MS Resume

Monday, June 18

MS 1. Recent advances in matrix functions
Organizer: Edvin Deadman
University of Manchester, UK
Organizer: Nicholas J. Higham
University of Manchester, UK

Matrix functions are of growing interest in science, engineering and the social sciences, due to the succinct and insightful way they allow problems to be formulated and solutions to be expressed. Many challenges remain in the computation of matrix functions. This minisymposium focuses on some recent advances, including preservation of structure, convergence of iterations, and design of algorithms that exploit modern computer architectures.

11:00–11:25 Computational issues related to the geometric mean of structured matrices
Dario A. Bini, Università di Pisa, Italy; Bruno Iannazzo, Università di Perugia, Italy

11:25–11:50 Efficient, communication-minimizing algorithms for the symmetric eigenvalue decomposition and the singular value decomposition
Yuji Nakatsukasa, University of Manchester; Nicholas J. Higham, University of Manchester

11:50–12:15 The Padé approximation and the matrix sign function
Krystyna Zietak, Wrocław University of Technology

12:15–12:40 A recursive blocked Schur algorithm for computing the matrix square root
Edvin Deadman, The University of Manchester / NAG; Nicholas J. Higham, University of Manchester; Rui Ralha, University of Minho, Portugal

Monday, June 18

MS 2. Methods for Toeplitz matrices and their application
Organizer: Matthias Bolten
University of Wuppertal, Germany

Many applications, e.g., in image processing, physics or finance, lead to Toeplitz matrices, i.e. matrices with constant entries on the diagonals. The Toeplitz structure and the associated generating symbol allows for the rigorous analysis of the methods used within the applications, including iterative methods like multigrid methods or methods to compute matrix functions. Many of these results carry over to block matrices with Toeplitz structure, as well. Within this minisymposium new developments regarding methods for Toeplitz systems will be presented. Further, applications for Toeplitz matrices and Toeplitz-block matrices are shown.

11:00–11:25 Toeplitz operators with matrix-valued symbols and some (unexpected) applications
Stefano Serra Capizzano, Università dell’Insubria -sede di Como

11:25–11:50 Fast approximation to the Toeplitz matrix exponential
Hai-Wei Sun, University of Macau

11:50–12:15 Matrix algebras sequences can be spectrally equivalent with ill-conditioned Toeplitz ones
Paris Vassalos, Athens University of Economics and Business; Dimitrios Noutsos, University of Ioannina

12:15–12:40 Aggregation-based multigrid methods for Toeplitz matrices
Matthias Bolten, University of Wuppertal; Marco Donatelli, Università dell’Insubria sede di Como; Thomas Huckle, Technische Universität München

Monday, June 18

MS 3. Matrix factorizations and applications
Organizer: Michael Tsatsomeros
Washington State Universiy, USA
Organizer: Rafael Cantó
Universitat Politècnica de València, ES

Factorizations of matrices play a crucial and diverse role in applied linear algebra. They typically lead to the development of numerical methods and theoretical understanding of diverse concepts in statistics, optimization, economics and others. In this minisymposium we assemble four talks on different types and applications of matrix factorizations. Particular attention will be paid to bidiagonal factorizations of some classes of matrices, the Cholesky full rank factorization for rank deficient matrices, the SVD decomposition with a number of related applications and a nonnegative matrix factorization.

11:00–11:25 Classes of matrices with bidiagonal factorization
Álvaro Barreras, Universidad de Zaragoza; J.M. Peña, Univ. de Zaragoza

11:25–11:50 Cholesky factorization for singular matrices
Rafael Cantó, Universitat Politècnica de València; A.M. Urbano, Univ. Politècnica de València; M.J. Peláez, Univ. Católica del Norte

11:50–12:15 Applications of the singular value decomposition to perturbation theory of eigenvalues of matrix polynomials
Panayiotis Psarrakos, National Technical University of Athens; N. Papathanasiou, National Technical Univ. of Athens

12:15–12:40 On reduced rank nonnegative matrix factorization for symmetric nonnegative matrices
Minerva Catral, Xavier University; L. Han, Univ. of Michigan-Flint; M. Neumann, Univ. of Connecticut; R.J. Plemmons, Wake Forest Univ.

Monday, June 18

MS 4. Algorithms on manifolds of low-rank matrices and tensors
Organizer: Bart Vandereycken
École Polytechnique Fédérale de Lausanne, Switzerland
Organizer: Pierre-Antoine Absil
Université catholique de Louvain, Belgium

This minisymposium concerns numerical algorithms on manifolds of tensors and matrices with certain rank structures. While exploiting rank is standard in numerical linear algebra, low-rank algorithms are usually based on techniques that are difficult to analyze. On the other hand, considering the set of fixed rank matrices/tensors as a smooth manifold provides a differential geometric framework for deriving and analyzing such low-rank algorithms. The speakers present recent developments in the field of pseudospectra, model reduction and high-dimensional equations. They show how such a differential geometric approach leads to efficient numerical algorithms and point out the advantages compared to more standard approaches.

11:00–11:25 Low rank dynamics for computing extremal points of real and complex pseudospectra
Nicola Guglielmi, Università di L’Aquila; Christian Lubich, Universität Tübingen

11:25–11:50 Parametric model order reduction using stabilized consistent interpolation on matrix manifolds
David Amsallem, Stanford University; Charbel Farhat, Stanford University

11:50–12:15 Treatment of high-dimensional problems by low-rank manifolds of tensors
Thorsten Rohwedder, Technische Universität Berlin

12:15–12:40 Local convergence of alternating optimization of multivariate functions in the presence of scaling indeterminacies
André Uschmajew, Technische Universität Berlin

Monday, June 18

MS 5. Advances in algebraic multigrid -New approaches and applications
Organizer: Irad Yavneh
Institute of Technology, Israel
Organizer: Eran Treister
Institute of Technology, Israel

Algebraic Multigrid (AMG) methods have long been recognized for their efficiency as solvers of sparse systems of equations, mainly such that arise from discretizations of PDEs. However, when it comes to solving more general algebraic systems, some drawbacks are evident in the classical methods. Consequently, a great effort is invested in extending the applicability of AMG methods for the solution of new and more complicated problems. This minisymposium focusses on the development of new AMG algorithms for solving or preconditioning linear systems arising in practical applications. Examples of such applications are found in numerical models used in computer networks, flow simulations, and elasticity.

11:00–11:25 Algebraic collocation coarse approximation multigrid
Eran Treister, Institute of Technology; Ran Zemach, Technion; Irad Yavneh, Technion

11:25–11:50 Energy-minimization interpolation for adaptive algebraic multigrid
Jacob B. Schroder, Lawrence Livermore National Laboratory; Robert D. Falgout, Lawrence Livermore National Laboratory

11:50–12:15 Algebraic multigrid (AMG) for complex network calculations
Geoffrey D. Sanders, Lawrence Livermore National Laboratory; Van Emden Henson, Lawrence Livermore National Laboratory; Panayot S. Vassilevski, Lawrence Livermore National Laboratory

12:15–12:40 The polynomial of best uniform approximation to 1/x as smoother in two grid methods
Ludmil T. Zikatanov, The Pennsylvania State University; Johannes Kraus, RICAM, Austria; Panayot S. Vassilevski, Lawrence Livermore National Laboratory

Monday, June 18

MS 6. Recent advances in fast iterative solvers -Part I of II
Organizer: Chen Greif
The University of British Columbia, Canada
Organizer: Alison Ramage
University of Strathclyde, UK

This two-session minisymposium concerns the solution of large and sparse linear systems using iterative solvers. We will address a variety of timely themes that pertain to preconditioning, convergence properties of solvers, and relevant applications. Specific topics include new preconditioned iterative schemes, the analysis of norms and spectral properties for measuring convergence of iterative solvers, and applications in fluid flow and liquid crystal.

11:00–11:25 Challenges in analysis of Krylov subspace methods
Zdenek Strakos, Charles University in Prague and Academy of Science of the Czech Republic; Jörg Liesen, Technical University of Berlin

11:25–11:50 Updating preconditioners for parameterized systems
Eric de Sturler, Virginia Tech; Sarah Wyatt, Virginia Tech; Serkan Gugercin, Virginia Tech

11:50–12:15 Efficient preconditioning techniques for two-phase flow simulations
Maya Neytcheva, Uppsala University; Owe Axelsson, Academy of Sciences of the Czech Republic; Petia Boyanova, Uppsala University; Martin Kronbichler, Uppsala University; Xunxun Wu, Uppsala University

12:15–12:40 Preconditioners in liquid crystal modelling
Alison Ramage, University of Strathclyde; Chris Newton, Hewlett-Packard Laboratories

Monday, June 18

MS 7. Application of statistics to numerical linear algebra algorithms -Part I of II
Organizer: Marc Baboulin
INRIA Saclay Île-de-France and University Paris-Sud, France
Organizer: Haim Avron
IBM T. J. Watson Research Center, USA

The last several years saw many new algorithms in applied linear algebra employing statistical methods. This increased interest is motivated by the fact that the resulting algorithms are able to outperform deterministic methods while still providing very accurate results. This mini-symposium will address innovative statistical approaches that accelerate significantly the solution of either dense or sparse linear systems and also enable us to estimate the conditioning of the solution. The speakers will also present several applications of randomized algorithms in numerical linear algebra including low rank approximations, numerical issues and how these algorithms adapt to large-scale parallel environment.

11:00–11:25 Fast linear system solvers based on randomization techniques
Marc Baboulin, Inria Saclay Île-de-France and University Paris-Sud, France; Dulceneia Becker, University of Tennessee, USA; Jack Dongarra, University of Tennessee, USA; Stanimire Tomov, University of Tennessee, USA

11:25–11:50 Numerical issues in randomized algorithms
Ilse Ipsen, North Carolina State University, USA

11:50–12:15 Near-optimal column based matrix reconstruction
Christos Boutsidis, IBM T. J. Watson Research Center, USA; Petros Drineas, Rensselaer Polytechnic Institute, USA; Malik Magdon-Ismail, Rensselaer Polytechnic Institute, USA

12:15–12:40 Numerical experiments with statistical condition estimation
Alan J. Laub, University of California Los Angeles, USA

Monday, June 18

MS 8. Rational Krylov methods: analysis and applications -Part I of II
Organizer: Vladimir Druskin
Schlumberger–Doll Research, USA
Organizer: Stefan Güttel
University of Oxford, UK

Rational Krylov spaces are a natural generalization of polynomial Krylov spaces to rational functions. In the last years, rational Krylov methods have proven to be useful tools for a variety of problems, such as the efficient solution of linear and nonlinear eigenvalue problems or matrix equations, in model order reduction, or the computation of matrix functions. This minisymposium brings together leading experts in the analysis and application of these methods, providing a lively forum on this central research topic of numerical linear algebra.

11:00–11:25 Solving Sylvester equations through rational Galerkin projections
Bernhard Beckermann, University of Lille

11:25–11:50 Stability-corrected spectral Lanczos decomposition algorithm for wave propagation in unbounded domains
Rob Remis, Delft University of Technology; Vladimir Druskin, Schlumberger–Doll Research

11:50–12:15 Generalized rational Krylov decompositions
Stefan Güttel, University of Oxford

12:15–12:40 Interpolatory model reduction strategies for nonlinear parametric inversion
Serkan Gugercin, Virginia Tech.; Christopher A. Beattie, Virginia Tech.; Saifon Chaturantabut, Virginia Tech.; Eric de Sturler, Virginia Tech.; Misha E. Kilmer, Tufts University

Monday, June 18

MS 9. New trends in tridiagonal matrices -Part I of II
Organizer: Natália Bebiano
University of Coimbra, Portugal

Tridiagonal matrices emerge in plenty of applications in science and engineering. They are used for solving a variety of problems in disparate contexts. Beyond their several applications seldom discussed, the methods, techniques, and theoretical framework used in this research field make it very interesting and challenging. In this forum of discussion, recent developments in the area are focused and new approaches and perspectives are searched.

11:00–11:25 Direct and inverse problems on pseudo-Jacobi matrices
Natália Bebiano, University of Coimbra, Portugal; Susana Furtado, University of Porto, Portugal; J. da Providência, University of Coimbra, Portugal

11:25–11:50 Schwartz’s matrices and generalized Hurwitz polynomials
Mikhail Tyaglov, Technische Universität Berlin, Germany

11:50–12:15 On the Moore-Penrose inverse of singular, symmetric and periodic Jacobi M-matrices
Andrés M. Encinas, Enrique Bendito, Ángeles Carmona and Margarida Mitjana, Universitat Politècnica de Catalunya, Spain

12:15–12:40 The commutant of the tridiagonal pattern
Charles R. Johnson, College of William and Mary, Williamsburg, USA

Monday, June 18

MS 10. Numerical algorithms for switching systems: from theory to applications
Organizer: Nicola Guglielmi
Universita degli Studi dell’ Aquila, Italy
Organizer: Raphaël Jungers
FNRS and UCLouvain, Belgium

In the past decade much progress has been achieved in the understanding of switching linear systems, and the development of algorithms to control/optimize these systems has received a strong impulse. On the one hand many fundamental theoretical issues have been investigated and partly settled. On the other hand, many applications have emerged, which can be cast as switching systems. These applications touch upon many different fields of engineering, from decentralized control to drug treatment optimization. The goal of the workshop is to present these two facets from a linear algebra perspective, and investigate the gap between theory and practice.

15:00–15:25 Observer design for hybrid systems
M. D. Di Benedetto, University of L’Aquila

15:25–15:50 About polynomial instability for linear switched systems
P. Mason, CNRS; Y. Chitour, University of Paris Sud; M. Sigalotti, INRIA Saclay

15:50–16:15 Stability and stabilization of positive switched systems: state of the art and open problems
M.E. Valcher, University of Padova; E. Fornasini, University of Padova

16:15–16:40 The joint spectral radius for semigroups generated by switched differential algebraic equations
F. Wirth, University of Würzburg; S. Trenn, Technical University of Kaiserslautern

Monday, June 18

MS 11. Recent advances in fast iterative solvers -Part II of II
Organizer: Chen Greif
The University of British Columbia, Canada
Organizer: Alison Ramage
University of Strathclyde, UK

This two-session minisymposium concerns the solution of large and sparse linear systems using iterative solvers. We will address a variety of timely themes that pertain to preconditioning, convergence properties of solvers, and relevant applications. Specific topics include new preconditioned iterative schemes, the analysis of norms and spectral properties for measuring convergence of iterative solvers, and applications in fluid flow and liquid crystal.

15:00–15:25 Combination preconditioning of saddle-point systems for positive definiteness
Andy Wathen, Oxford University; Jennifer Pestana, Oxford University

15:25–15:50 Preconditioned iterative methods for nonsymmetric matrices and nonstandard inner products
Jennifer Pestana, Oxford University; Andy Wathen, Oxford University

15:50–16:15 Multi-preconditioned GMRES
Tyrone Rees, Rutherford Appleton Laboratory; Chen Greif, The University of British Columbia; Daniel B. Szyld, Temple University

16:15–16:40 Bounds on the eigenvalues of indefinite matrices arising from interior-point methods
Chen Greif, The University of British Columbia; Erin Moulding, The University of British Columbia; Dominique Orban, Ecole Polytechnique de Montreal

Monday, June 18

MS 12. Application of statistics to numerical linear algebra algorithms -Part II of II
Organizer: Marc Baboulin
INRIA Saclay Île-de-France and University Paris-Sud, France
Organizer: Haim Avron
IBM T. J. Watson Research Center, USA

The last several years saw many new algorithms in applied linear algebra employing statistical methods. This increased interest is motivated by the fact that the resulting algorithms are able to outperform deterministic methods while still providing very accurate results. This mini-symposium will address innovative statistical approaches that accelerate significantly the solution of either dense or sparse linear systems and also enable us to estimate the conditioning of the solution. The speakers will also present several applications of randomized algorithms in numerical linear algebra including low rank approximations, numerical issues and how these algorithms adapt to large-scale parallel environment.

15:00–15:25 Spectral graph theory, sampling matrix sums, and near-optimal SDD solvers
Ioannis Koutis, University of Puerto Rico; Gary Miller, Carnegie Mellon University, USA; Richard Peng, Carnegie Mellon University, USA

15:25–15:50 Implementation of a randomization algorithm for dense linear algebra libraries
Dulceneia Becker, University of Tennessee, USA; Marc Baboulin, Inria Saclay Île-de-France and University Paris-Sud, France; Jack Dongarra, University of Tennessee, USA

15:50–16:15 Implementing randomized matrix algorithms in large-scale parallel environments
Michael W. Mahoney, Stanford University, USA

16:15–16:40 Random sampling preconditioners
Haim Avron, IBM T. J. Watson Research Center, USA; Sivan Toledo, Tel-Aviv University, Israel

Monday, June 18

MS 13. Rational Krylov methods: analysis and applications -Part II of II
Organizer: Vladimir Druskin
Schlumberger–Doll Research, USA
Organizer: Stefan Güttel
University of Oxford, UK

Rational Krylov spaces are a natural generalization of polynomial Krylov spaces to rational functions. In the last years, rational Krylov methods have proven to be useful tools for a variety of problems, such as the efficient solution of linear and nonlinear eigenvalue problems or matrix equations, in model order reduction, or the computation of matrix functions. This minisymposium brings together leading experts in the analysis and application of these methods, providing a lively forum on this central research topic of numerical linear algebra.

15:00–15:25 Rational Krylov methods for nonlinear matrix problems
Karl Meerbergen, KU Leuven; Roel Van Beeumen, KU Leuven; Wim Michiels, KU Leuven

15:25–15:50 Block Gauss and anti-Gauss quadrature rules with application to networks
Lothar Reichel, Kent State University; David Martin, Kent State University

15:50–16:15 On optimality of rational Krylov based low-rank approximations of large-scale matrix equations
Tobias Breiten, Max Planck Institute for Dynamics of Complex Technical Systems; Peter Benner, Max Planck Institute for Dynamics of Complex Technical Systems

16:15–16:40 Inverse problems for large-scale dynamical systems in the H2-optimal model reduction framework
Mikhail Zaslavsky, Schlumberger–Doll Research; Vladimir Druskin, Schlumberger–Doll Research; Valeria Simoncini, University of Bologna

Monday, June 18

MS 14. New trends in tridiagonal matrices -Part II of II
Organizer: Carlos Fonseca
University of Coimbra, Portugal

Tridiagonal matrices emerge in plenty of applications in science and engineering. They are used for solving a variety of problems in disparate contexts. Beyond their several applications seldom discussed, the methods, techniques, and theoretical framework used in this research field make it very interesting and challenging. In this forum of discussion, recent developments in the area are focused and new approaches and perspectives are searched.

15:00–15:25 On generalized Jacobi matrices which are symmetric in Krein spaces
Maxim Derevyagin, Technische Universität Berlin, Germany

15:25–15:50 On the characteristic function for Jacobi matrices
Pavel Stovícek, Czech Technical University, Czech Republic

15:50–16:15 Tridiagonal matrices in comb filters
Jesús Gutiérrez-Gutiérrez, Universidad de Navarra, Spain

16:15–16:40 The nullity theorem: forecasting structures in the inverses of sparse matrices
Raf Vandebril, K.U. Leuven, Belgium

Monday, June 18

MS 15. Application of compressed sensing in Bio-Medicine
Organizer: Amir Niknejad
The College of Mount Saint Vincent, USA

The past decade have witnessed burgeoning research activity in the area of compressed sensing and sparse approximation. This minisymposium is devoted to the mathematical aspects of sparsity in undetermined linear systems and its applications in bio-medicine. It will bring together Scientists who use compressive sensing in their respected fields. The focus is on problems arising in molecular biology and bio-medicine. Most application is related to the processing of biological data, Drug Discovery, and neuro imaging. This minisymposium is intended as a workshop for strengthening communication between computational biologists and the linear algebra community for fostering collaborations.

15:00–15:25 Evaluation of compressed sensing impact in cardiac signals processing and transmission
Eduardo Pinheiro, Instituto de Telecomunicaes Instituto Superior Tcnico, Lisboa, Portugal

15:25–15:50 Compressive sensing in drug discovery
Marcus Weber, Zuse Institute Berlin (ZIB), Germany

15:50–16:15 Reconstruction of bacterial communities using sparse representation
Or Zuk, Broad Institute, Cambridge, USA

16:15–16:40 Sensing genome via factorization
Amir Niknejad, College of Mount Saint Vincent,New York, USA

Monday, June 18

MS 16. Preconditioning of non-normal linear systems arising in scattering problems
Organizer: Kees Vuik and Neil Budko
Delft University of Technology, The Netherlands

The scattering of waves on inhomogeneous objects and many other important problems are described by large linear systems with non-normal matrices. A few iterative methods that can cope with such systems often suffer from an extremely slow convergence. In recent years there has been some progress in understanding the reasons behind this behavior and several efficient preconditioners have been proposed ranging from the deflation of the largestmagnitude eigenvalues, to regularization, the approximate factorization of the inverse, and shifted Laplacians. In our minisymposium we review the application of these methods to differential and integral equations arising in scattering problems.

15:00–15:25 Approximate deflation preconditioning methods for penetrable scattering problems
Josef Sifuentes, New York University; Mark Embree, Rice University

15:25–15:50 Direct approximate factoring of the inverse
Marko Huhtanen, University of Oulu; Mikko Byckling, CERFACS

15:50–16:15 Regularization of singular integral operators as a preconditioning strategy
Neil Budko, Delft University of Technology; Grigorios Zouros, National Technical University of Athens

16:15–16:40 High-order shifted Laplace preconditioners for wave equations
Xavier Antoine, University of Lorraine; Christophe Geuzaine, University of Liège; Ibrahim Zangré, University of Lorraine

Monday, June 18

MS 17. Markov chains
Organizer: Jeffrey J. Hunter
Auckland University of Technology, New Zealand
Organizer: Stephen J. Kirkland
National University of Ireland, Ireland

The mini-symposium will feature recent research activity in the area of Markov chains, with a focus on some key properties and applications. Interpretations of Kemeny’s constant, the interaction between random walks on graphs and electrical networks, and matrix-based approaches, all offer significant opportunities for new advances. These approaches will be considered in several contexts, including hitting and mixing times, ergodicity, Laplacians, Hamiltonian cycles, generalized inverses, perturbation and sensitivity analysis, computational procedures, the column sums of a transition matrix, and different matrix representations. The mini-symposium is expected to encourage further dialogue between the theory and applications of Markov chains.

15:00–15:25 Markov chain properties in terms of column sums of the transition matrix
Jeffrey J. Hunter, Auckland University of Technology, Auckland, New Zealand

15:25–15:50 Hamiltonian cycle problem and Markov chains
Jerzy Filar, Flinders University, Bedford Park, SA, Australia

15:50–16:15 Inequalities for functions of transition matrices
Iddo Ben-Ari, University of Connecticut, Storrs, CT, United States of America

16:15–16:40 Compartmental systems and computation of their stationary probability vectors
Ivo Marek, Czech Institute of Technology, Praha, Czech Republic

Tuesday, June 19

MS 18. Preconditioning for PDE-constrained optimization -Part I of II
Organizer: Martin Stoll
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Germany
Organizer: Andy Wathen
Numerical Analysis Group, United Kingdom

The solution of optimization problems with constraints given by partial differential equations is a challenging problem for numerical analysts. Whether the constraint is linear or nonlinear, at the heart of the optimization procedure lies the solution of linear systems that are often very large, sparse and structured. Our minisymposium is aimed at providing insights into recent developments with respect to Krylov subspace methods that in conjunction with efficient preconditioning techniques provide a robust and flexible framework for solving PDE-constrained optimization problems.

11:00–11:25 Structural spectral properties of symmetric saddle point problems
Valeria Simoncini, Università di Bologna, Italy, Wolfgang Krendl and Walter Zulehner, Johannes Kepler University, Austria

11:25–11:50 Preconditioned iterative methods for Stokes and Navier-Stokes control problems
John Pearson, University of Oxford, UK

11:50–12:15 Preconditioners for elliptic optimal control problems with inequality constraints
Walter Zulehner and Markus Kollmann, Johannes Kepler University, Austria

12:15–12:40 Nearly optimal block preconditioners for block two-by-two linear systems
Zhong-Zhi Bai, Chinese Academy of Sciences, China

Tuesday, June 19

MS 19. Matrices and graphs -Part I of  II
Organizer: Leslie Hogben
Iowa State University, USA
Organizer: Stephen Kirkland
National University of Ireland Maynooth, Ireland

Interactions between matrices and graphs now play a vital role in both matrix theory and graph theory, and have applications to a variety of fields. This mini-symposium will present recent results related to the synergistic relationship between matrices and graphs, including properties of matrices having a nonzero pattern described by a given graph, and information about a graph provided by specific matrices associated with the graph. Applications to control of quantum systems and other areas will be presented.

11:00–11:25 (0, 1) matrices and the analysis of social networks
Steve Kirkland, National University of Ireland Maynooth

11:25–11:50 Necessary and sufficient conditions for a Hamiltonian graph
Irene Sciriha, University of Malta; Domingos Moreira Cardoso, Univ. de Aveiro

11:50–12:15 On the eigenvalues of symmetric matrices associated with graphs
Miriam Farber, Technion

12:15–12:40 An extension of the polytope of doubly stochastic matrices
Richard Brualdi, University of Wisconsin-Madison; Geir Dahl, University of Oslo

Tuesday, June 19

MS 20. Tensor based methods for high dimensional problems in scientific computing -Part I of II
Organizer: A. Falcó
Universidad de Alicante, Spain
Organizer: A. Nouy
LUNAM Université, Ecole Centrale Nantes, France

The use of tensor product approximations is receiving a growing interest in numerical analysis for the solution of problems defined in high-dimensional tensor spaces, such as PDEs arising in stochastic calculus (e.g. the Fokker-Planck equation), variational problems, approximation theory, stochastic parametric PDEs arising in uncertainty quantification, and quantum chemistry. This minisymposium focuses on recent advances in this topic. In particular, the scope of this proposal includes: (a) High dimensional PDEs (deterministic or stochastic) or other operator equations in tensor format. (b) Iterative methods using tensor approximations. Preconditioning issues, convergence analysis. (c) Alternative definitions and algorithms for tensor decompositions. (d) Functional Analysis approach of tensor methods. (e) Applications of tensor methods in real-life problems.

11:00–11:25 Optimal a priori tensor decomposition for the solution of high dimensional problems
Anthony Nouy, LUNAM Université, Ecole Centrale Nantes

11:25–11:50 Application of the Proper Generalized Decomposition (PGD) to 3D cracked plates and estimation of the discretization error 
Eugenio Giner, CITV, UPV

11:50–12:15 A tensor calculus approach for Bézier shape deformation
Lucía Hilario, U. CEU Cardenal Herrera

12:15–12:40 Tensor approximation methods for parameter identification
Hermann G. Matthies, Alexander Litvinenko, Bojana Rosíc and Oliver Pajonk, Institute of Scientific Computing, TU Braunschweig

Tuesday, June 19

MS 21. Reducing communication in linear algebra -Part I of II
Organizer: Aydın Buluç
Lawrence Berkeley National Laboratory
Organizer: Oded Schwartz
University of California, Berkeley

Performance scaling of linear algebra kernels is limited by the cost of data movement between memory hierarchy levels and between processors in a parallel setting. Communication efficient linear algebra kernels will help scientific computing reach exascale, and accelerate non-numerical applications that rely on linear algebra such as machine learning, data mining, and graph analysis. This minisymposium discusses new dense and sparse linear algebra algorithms that move asymptotically less data, lower bounds on the amount of communication needed for various problems, and practical implementations that outperform conventional codes by reducing communication.

11:00–11:25 Communication-optimal parallel algorithm for Strassen’s matrix multiplication
Oded Schwartz, Grey Ballard, James Demmel, Olga Holtz and Benjamin Lipshitz, UC Berkeley

11:25–11:50 A communication-avoiding symmetric-indefinite factorization
Sivan Toledo, Tel-Aviv University; Grey Ballard and James Demmel, UC Berkeley; Alex Druinsky and Inon Peled, Tel-Aviv University; Oded Schwartz, UC Berkeley

11:50–12:15 LU factorization with panel rank revealing pivoting and its communication avoiding version
Amal Khabou, INRIA Saclay -Île de France; James Demmel, UC Berkeley; Laura Grigori, INRIA Saclay -Ile de France; Ming Gu, UC Berkeley

12:15–12:40 2.5D Algorithms for parallel dense linear algebra
Edgar Solomonik and James Demmel, UC Berkeley

Tuesday, June 19

MS 22. Linear algebra for inverse problems -Part I of II
Organizer: L. Reichel
Kent State University, USA
Organizer: H. Sadok
LMPA, Université du Littoral, France

Many problems in science and engineering require the determination of the cause of an observed effect. These problems often can be formulated as Fredholm integral equations of the first kind with a smooth kernel. Their discretization gives rise to linear systems of equations with a matrix whose singular values “cluster” at the origin and whose right-hand side is contaminated by error. The development and analysis of solution techniques for these kinds of problems is an active area of research, and much of this work is based on linear algebra. This minisymposium brings together leading experts on the development and analysis of solution methods for inverse problems. The presentations provide an overview of recent developments with an emphasis on the role of linear algebra.

11:00–11:25 Block-extrapolation methods for linear matrix ill-posed problem
K. Jbilou, Université du Littoral

11:25–11:50 Convergence properties of the GMRES and RRGMES methods for ill-posed problems
H. Sadok, Université du Littoral

11:50–12:15 Inverse problems for regularization matrices
Silvia Noschese, SAPIENZA Università di Roma; Lothar Reichel, Kent State University

12:15–12:40 Meshless regularization for the numerical computation of the solution of steady Burgers-type equations
A. Bouhamidi, Université du Littoral; M. Hached, Université du Littoral; K. Jbilou, Université du Littoral

Tuesday, June 19

MS 23. Modern matrix methods for large scale data and networks
Organizer: David F. Gleich
Purdue University, USA

Every few years, the new applications for matrix methods arise and challenge existing paradigms. The talks in this mini-symposium sample some of the research that has arisen out of new applications in large scale machine learning, network problems, and data analysis. Much of the research presented at this mini-symposium will have an interesting twist on a classical matrix problem – linear systems, least squares, or eigenvalues – that better fits the current problems.

11:00–11:25 Nonlinear eigenproblems in data analysis and graph partitioning
Matthias Hein, Saarland University

11:25–11:50 LSRN: a parallel iterative solver for strongly over-or under-determined systems
Xiangrui Meng, M. A. Saunders and M. W. Mahoney, Stanford University

11:50–12:15 Solving large dense linear systems with covariance matrices
Jie Chen, Argonne National Laboratory

12:15–12:40 Fast coordinate descent methods with variable selection for non-negative matrix factorization
Inderjit S. Dhillon and Cho-Jui Hsieh, The University of Texas at Austin

Tuesday, June 19

MS 24. Novel and synergetic algorithms for multicore and multinode architecture
Organizer: Olaf Schenk
University of Lugano, Switzerland
Organizer: Ping Tak Peter Tang
Intel Corporation

The advent of parallel computers from multiple CPUs to, more recently, multiple processor cores within a single CPU has continued to spur innovative linear algebra algorithms. This minisymposium aims to present a number of works that not only exhibit new algorithmic ideas suitable for these modern computer architecture, but also present interesting synergies among themselves in several levels. Some can act as a plug-and-play component to enable others; the enabled algorithms can produce components to enable the enablers in turn; and special algorithmic developments were undertaken to enrich this ecosystem.

11:00–11:25 Novel and synergetic linear algebra algorithms on multicore and multinode architecture
Ping Tak Peter Tang, Intel Corporation

11:25–11:50 PSPIKE – A hybrid sparse linear system solver
Olaf Schenk, University of Lugano, Switzerland; Ahmed Sameh, Purdue University

11:50–12:15 Eigensolver Based Reordering and Parallel TraceMIN
Murat Manguogluo, Middle East Technical University; Faisal Saied and Ahmed Sameh, Purdue University

12:15–12:40 FEAST – A density matrix based eigensolver
Eric Polizzi, University of Massachusetts

Tuesday, June 19

MS 25. Direction preserving and filtering methods for solving sparse linear systems
Organizer: Laura Grigori
University Paris 11, France
Organizer: Frederic Nataf
Paris 6 University, France

This minisymposium reviews several results obtained in the recent years in developing direction preserving and filtering methods for solving sparse linear systems of equations. These methods have been studied in different contexts. For example, preconditioners that are identical with the input matrix given a set of vectors are able to deal efficiently with low frequency modes. For multigrid methods, the filtering allows to preserve in the coarse space several directions of interest. The talks discuss this approach for two level domain decomposition methods, multigrid methods, and approached block factorizations.

11:00–11:25 Algebraic two-level domain decomposition methods
Frederic Nataf, Paris 6 University, France; Pascal Have, IFP, France; Roland Masson, University of Nice, France; Mikolaj Szydlarski and Tao Zhao, University of Paris 6, France

11:25–11:50 Filtering solvers
G. Wittum, University of Frankfurt, Germany

11:50–12:15 Bootstrap algebraic multigrid
Karsten Kahl, University of Wuppertal, Germany; James Brannick, Pennsylvania State University, USA

12:15–12:40 Block filtering decomposition
Laura Grigori, INRIA Saclay, University of Paris 11, France; Frederic Nataf, University of Paris 6, France; Riadh Fezzanni, INRIA Saclay, University of Paris 11, France;

Tuesday, June 19

MS 26. Advances in Krylov subspace methods
Organizer: Sou-Cheng Choi
The University of Chicago, US

Krylov subspace methods have a long illustrious history in numerical linear algebra. Acronyms like BiCG-Stab, CG, GMRES, LSQR, MINRES, QMR, etc, have become part of the standard vocabulary of every numerical analyst. It is somewhat surprising that major advances are still being made to a subject so classical. This minisymposium brings together researchers who have made recent major breakthroughs in the development of Krylov subspace methods—new algorithms that fill existing gaps, better convergence and stability analyses, and novel adaptations for efficiency under alternative measures of computational costs (such as communication complexity).

11:00–11:25 The new challenges to Krylov subspace methods
Yousef Saad, The University of Minnesota, USA

11:25–11:50 Random shadow vectors in IDR(s): an explanation of its GMRES-like convergence
Peter Sonneveld, The Delft University of Technology

11:50–12:15 Truncated and inexact Krylov subspace methods for parabolic control problems
Daniel Szyld, The Temple University, USA ; X. Du, Alfred Univ., USA ; M. Sarkis, Worcester Polytechnic Inst., USA ; C. Schaerer, National Univ. of Asuncion, Paraguay

12:15–12:40 Convergence of iterative solution algorithms for least-squares problems
David Titley-Peloquin, The University of Oxford; S. Gratton, ENSEEIHT; P. Jiranek, CERFACS

Tuesday, June 19

MS 27. Preconditioning forPDE-constrained optimization -Part II of II
Organizer: Martin Stoll
Computational Methods in Systems and Control Theory Max Planck Institute for Dynamics of Complex Technical Systems, Germany
Organizer: Andy Wathen
Mathematical Institute, United Kingdom

The solution of optimization problems with constraints given by partial differential equations is a challenging problem for numerical analysts. Whether the constraint is linear or nonlinear, at the heart of the optimization procedure lies the solution of linear systems that are often very large, sparse and structured. Our minisymposium is aimed at providing insights into recent developments with respect to Krylov subspace methods that in conjunction with efficient preconditioning techniques provide a robust and flexible framework for solving PDE-constrained optimization problems.

15:00–15:25 On linear systems arising in trust-region methods
Susann Mach and Roland Herzog, University of Technology Chemnitz, Germany

15:25–15:50 Preconditioning for PDE-constrained optimization using proper orthogonal decomposition
Ekkehard Sachs and Xuancan Ye, Universitt Trier, Germany

15:50–16:15 Preconditioning for Allen-Cahn problems with non-local constraints
Luise Blank, University of Regensburg; Martin Stoll, Max Planck Institute for Dynamics of Complex Technical Systems, Germany; Lavinia Sarbu

16:15–16:40 A one-shot approach to time-dependent PDE control
Martin Stoll, Max Planck Institute for Dynamics of Complex Technical Systems, Germany, Andy Wathen and John Pearson; University of Oxford, UK

Tuesday, June 19

MS 28. Matrices and graphs -Part II of II
Organizer: Leslie Hogben
Iowa State University, USA
Organizer: Stephen Kirkland
National University of Ireland Maynooth, Ireland

Interactions between matrices and graphs now play a vital role in both matrix theory and graph theory, and have applications to a variety of fields. This mini-symposium will present recent results related to the synergistic relationship between matrices and graphs, including properties of matrices having a nonzero pattern described by a given graph, and information about a graph provided by specific matrices associated with the graph. Applications to control of quantum systems and other areas will be presented.

15:00–15:25 Parameters related to maximum nullity, zero forcing number, and tree-width of a graph
Leslie Hogben, Iowa State University and American Institute of Mathematics; and others (listed with abstract)

15:25–15:50 Colin de Verdière numbers of chordal and split graphs
Felix Goldberg, National University of Ireland Maynooth

15:50–16:15 Kochen-Specker sets and the rank-1 quantum chromatic number
Simone Severini, University College London

16:15–16:40 On the null vectors of graphs
Shaun Fallat, University of Regina

Tuesday, June 19

MS 29. Tensor based methods for high dimensional problems in scientific computing -Part II of II
Organizer: A. Falcó
Universidad de Alicante, Spain
Organizer: A. Nouy
LUNAM Université, Ecole Centrale Nantes, France

The use of tensor product approximations is receiving a growing interest in numerical analysis for the solution of problems defined in high-dimensional tensor spaces, such as PDEs arising in stochastic calculus (e.g. the Fokker-Planck equation), variational problems, approximation theory, stochastic parametric PDEs arising in uncertainty quantification, and quantum chemistry. This minisymposium focuses on recent advances in this topic. In particular, the scope of this proposal includes: (a) High dimensional PDEs (deterministic or stochastic) or other operator equations in tensor format. (b) Iterative methods using tensor approximations. Preconditioning issues, convergence analysis. (c) Alternative definitions and algorithms for tensor decompositions. (d) Functional Analysis approach of tensor methods. (e) Applications of tensor methods in real-life problems.

15:00–15:25 A greedy algorithm for the convergence of a Laplacian operators in the blind deconvolution problem
Pantaleón David Romero Sánchez, Universidad CEU-Cardenal Herrera, Spain

15:25–15:50 Algorithms for approximate inverse of operators for preconditioning systems of equations in tensor format
Loic Giraldi LUNAM Université; Anthony Nouy and Gregory Legrain, Université de Nante, France

15:50–16:15 Geometric structures in tensor representations
Antonio Falcó, Universidad de Alicante, Spain

Tuesday, June 19

MS 30. Reducing communication in linear algebra -Part II of II
Organizer: Aydın Buluç
Lawrence Berkeley National Laboratory, USA
Organizer: Oded Schwartz
University of California, USA

Performance scaling of linear algebra kernels is limited by the cost of data movement between memory hierarchy levels and between processors in a parallel setting. Communication efficient linear algebra kernels will help scientific computing reach exascale, and accelerate non-numerical applications that rely on linear algebra such as machine learning, data mining, and graph analysis. This minisymposium discusses new dense and sparse linear algebra algorithms that move asymptotically less data, lower bounds on the amount of communication needed for various problems, and practical implementations that outperform conventional codes by reducing communication.

15:00–15:25 Communication-avoiding sparse matrix-matrix multiplication
Aydın Buluç, LBNL; Grey Ballard, UC Berkeley; James Demmel, UC Berkeley; Laura Grigori, INRIA Saclay -Île de France; Oded Schwartz, UC Berkeley

15:25–15:50 Improving the stability of communication-avoiding Krylov subspace methods
Erin Carson, Nicholas Knight and James Demmel, UC Berkeley, USA

15:50–16:15 Hiding global synchronization latencies in Krylov methods for systems of linear equations
Pieter Ghysels and Wim Vanroose University of Antwerp, BE

16:15–16:40 Avoiding communication with hierarchical matrices
Nicholas Knight, Erin Carson and James Demmel, UC Berkeley, USA

Tuesday, June 19

MS 31. Linear algebra for inverse problems -Part II of II
Organizer: L. Reichel
Kent State University, USA
Organizer: H. Sadok
LMPA, Université du Littoral, France

Many problems in science and engineering require the determination of the cause of an observed effect. These problems often can be formulated as Fredholm integral equations of the first kind with a smooth kernel. Their discretization gives rise to linear systems of equations with a matrix whose singular values “cluster” at the origin and whose right-hand side is contaminated by error. The development and analysis of solution techniques for these kinds of problems is an active area of research, and much of this work is based on linear algebra. This minisymposium brings together leading experts on the development and analysis of solution methods for inverse problems. The presentations provide an overview of recent developments with an emphasis on the role of linear algebra.

15:00–15:25 Implicit filtering methods for inverse problems
J. G. Nagy, Emory University; A. Cornelio, University of Modena and Reggio Emilia; E. L. Piccolomini, University of Bologna

15:25–15:50 Iterative reconstruction methods for adaptive optics
R. Ramlau, Kepler University

15:50–16:15 Approximated nonstationary iterated Tikhonov with application to image deblurring
M. Donatelli, University of Insubria; M. Hanke, University of Mainz

16:15–16:40 On the Richardson-Lucy method for image restoration
F. Sgallari, University of Bologna; M. K. Khan, Kent State University; S. Morigi, University of Bologna; L. Reichel, Kent State University

Tuesday, June 19

MS 32. Orderings in sparse matrix computation
Organizer: Iain S. Duff
Rutherford Appleton Laboratory, UK
Organizer: Esmond G. Ng
Lawrence Berkeley National Laboratory, USA

Ordering in sparse matrix computation refers to the problem of permuting the rows and columns of a sparse matrix to achieve certain objectives. It is an integral step in sparse matrix computation. For example, it is desirable to find permutations so that the number of nonzeros created or the number of operations is small in a sparse matrix factorization. In iterative methods, orderings are important in reducing communication in parallel implementations. In this minisymposium, we feature some recent work on sparse matrix orderings. Some of the talks will focus on algorithmic development, while others will investigate the theoretical aspect.

15:00–15:25 Orderings and solvers for “non-uniform sparse matrices”
Edmond Chow and Oguz Kaya, Georgia Institute of Technology, USA

15:25–15:50 On hypergraph partitioning based ordering methods for sparse matrix factorization
Bora Uçar, CNRS and ENS Lyon; Iain S. Duff, Rutherford Appleton Laboratory; Johannes Langguth, ENS Lyon

15:50–16:15 Orderings Governed by numerical factorization
Iain S. Duff and Mario Arioli, Rutherford Appleton Laboratory

16:15–16:40 Reordering sparse Cholesky factorization: minimum fill vs. minimum FLOP count
Robert Luce, Technical University of Berlin; Esmond G. Ng, Lawrence Berkeley National Laboratory

Tuesday, June 19

MS 33. Moving from multicore to manycore in applied linear algebra
Organizer: Jens Saak
Max Planck Institute for Dyamics of Complex Technical Systems, Germany
Organizer: Alfredo Remón
Universidad Jaume I, Spain

During the last years, the evolution of graphics processors (GPUs) has extended their use to many scientific and engineering applications. In particular, their highly parallel architecture makes them suitable for vector operations and especially appealing for linear algebra (LA) applications. To leverage their potential, it is necessary to rethink numerical LA algorithms and codes. The impact of GPUs in LA has motivated the design of a number of recent LA libraries: CUBLAS, CUFFT, FLAME, MAGMA, … To illustrate these ongoing developments, we have chosen a handful of researchers that contributed in moving towards manycore computing during the recent years.

15:00–15:25 Parallel preconditioners and multigrid methods for sparse systems on GPUs
Jan-Philipp Weiss, Dimitar Lukarski and Vincent Heuveline, Karlsruhe Institute of Technology (KIT), Germany

15:25–15:50 Towards a GPU-accelerated direct sparse solver
Pablo Ezzatti and Alejandro Zinemanas, Univ. de la República, Uruguay

15:50–16:15 Unleashing the power of multicore DSPs for matrix computations. The FLAME approach
Francisco D. Igual, University Jaume I, Spain; Murtaza Ali, Texas Instruments, USA; Robert A. van de Geijn, The University of Texas at Austin, USA

16:15–16:40 High-performance genome studies
Lucas Beyer, Diego Fabregat-Traver and Paolo Bientinesi, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), Germany

Tuesday, June 19

MS 34. Least squares methods and applications
Organizer: Sanzheng Qiao
McMaster University1, Canada
Organizer: Yimin Wei
Fudan University, P.R. China

This minisymposium provides an overview of recent research in a wide range of topics in linear and nonlinear least squares problems, including block algorithms, applications in wireless communications, perturbation analysis, and preconditioning techniques

11:00–11:25 Block Gram–Schmidt algorithms with reorthogonalization
Jesse Barlow, Penn State University, USA

11:25–11:50 A numerical method for a mixed discrete bilinear least squares problem
Xiao-Wen Chang, McGill University, Canada

11:50–12:15 On condition numbers for constrained linear least squares problems
Huaian Diao, Northeast Normal University, P.R. China

12:15–12:40 SOR inner-iteration GMRES for underdetermined least squares problems
Keiichi Morikuni and Ken Hayami, The Graduate University for Advanced Studies, Japan

Wednesday, June 20

MS 35. Nonlinear eigenvalue problems
Organizer: K. Meerbergen
K.U. Leuven, Belgium
Organizer: W. Michiels
K.U. Leuven, Belgium
Organizer: C. Lecomte
University of Southampton, UK

The interest in nonlinear eigenvalue problems has increased significantly over the last few years. Recent contributions have focused on methods derived from residual inverse iteration and nonlinear Rayleigh quotient iteration, as well as Krylov methods for linear infinite dimensional problems and linearizations of polynomial eigenvalue problems. Those ideas show up as building blocks for solving non-linear non-polynomial eigenvalue problems.

11:00–11:25 Computable error bounds for nonlinear eigenvalue problems allowing for a minimax characterization
Heinrich Voss, Hamburg University of Technology, Germany; Kemal Yildiztekin, Hamburg University of Technology, Germany

11:25–11:50 A restarting technique for the infinite Arnoldi method
Elias Jarlebring, KTH -Royal institute of technology, Sweden; Karl Meerbergen, K.U.Leuven, Belgium; Wim Michiels, K.U.Leuven, Belgium

11:50–12:15 Robust successive computation of eigenpairs for nonlinear eigenvalue problems
Cedric Effenberger, EPF Lausanne, Switzerland

12:15–12:40 Triangularization of matrix polynomials
Leo Taslaman, University of Manchester, UK; Yuji Nakatsukasa, University of Manchester,UK; Franc¸oise Tisseur, University of Manchester, UK

Wednesday, June 20

MS 36. Hybrid solvers for sparse linear equations
Organizer: Iain S Duff
STFC Rutherford Appleton Laboratory, UK
Organizer: Luc Giraud
Joint INRIA-CERFACS Laboratory, France

There is now a recognition that neither direct nor iterative methods by themselves are capable of solving some of the really large challenging sparse systems coming from large scale simulation. In this minisymposium, we consider a range of solution techniques that combine direct and iterative solution approaches and show that they are capable of solving equations with over a billion unknowns. We consider methods based on domain decomposition and block iterative methods such as the Block Cimmino. Some of the contributions also study the implementation of such approaches on parallel architectures.

11:00–11:25 The augmented block-Cimmino distributed method
Mohamed Zenadi, ENSEEIHT-IRIT; Iain Duff, CERFACS and RAL; Ronan Guivarch, ENSEEIHT-IRIT; Daniel Ruiz, ENSEEIHT-IRIT

11:25–11:50 On a parallel hierarchical algebraic domain decomposition method for a large scale sparse linear solver
Luc Giraud, Inria, joint Inria-CERFACS Lab; Emmanuel Agullo, Inria; Abdou Guermouche, Bordeaux University; Jean Roman, Inria

11:50–12:15 A two-level Schwarz method for systems with high contrasts
Nicole Spillane, Université Pierre et Marie Curie; Victorita Dolean, Université de Nice-Sophia Antipolis; Patrice Hauret, MFP Michelin; Fréric Nataf, Université dé Pierre et Marie Curie; Clemens Pechstein, Johannes Kepler University; Robert Scheichl, University of Bath

12:15–12:40 A 3-level parallel hybrid preconditioner for sparse linear systems
Erik Boman, Sandia National Labs; Siva Rajamanickam, Sandia National Labs; Michael Heroux, Sandia National Labs; Radu Popescu, EPFL, Switzerland

Wednesday, June 20

MS 37. Optimization methods for tensor decomposition
Organizer: Hans De Sterck
University of Waterloo

Tensor decomposition has emerged as an important technique in a variety of application domains, which include signal processing, chemometrics, datamining, neuroscience, and many more. For many applications, (approximate) tensor decomposition can naturally be posed as an optimization problem, and there is significant current interest in how new tensor decomposition algorithms can be developed that originate from this optimization viewpoint, aiming to improve over existing approaches like alternating least-squares based methods, which are versatile but can be inefficient. This mini-symposium will highlight recent results on new optimization-based algorithms for several types of tensor decomposition problems.

11:00–11:25 Efficient algorithms for tensor decompositions
Laurent Sorber, KU Leuven; Marc Van Barel, KU Leuven; Lieven De Lathauwer, KU Leuven

11:25–11:50 Symmetric tensor decomposition via a power method for the generalized tensor eigenproblem
Jackson R. Mayo, Sandia National Laboratories; Tamara G. Kolda, Sandia National Laboratories

11:50–12:15 All-at-once optimization for coupled matrix and tensor factorizations
Evrim Acar, University of Copenhagen; Tamara G. Kolda, Sandia National Laboratories; Daniel M. Dunlavy, Sandia National Laboratories; Rasmus Bro, University of Copenhagen

12:15–12:40 An algebraic multigrid optimization method for low-rank canonical tensor decomposition
Killian Miller, University of Waterloo; Hans De Sterck, University of Waterloo

Wednesday, June 20

MS 38. Generalized inverses and applications -Part I of II
Organizer: Dragana S. Cvetkovic-Ilic
University of Nis, Serbia
Organizer: Néstor Thome
Universitat Politècnica de València, Spain
Organizer: Yimin Wei
Fudan University, P.R. China

Generalized inverses was first introduced on operators (Fredholm (1903), Hilbert (1904)) and later on matrices (Moore (1920), Penrose (1955)). The most important fact was its conection with least-squares method. Theory, applications and computational methods of generalized inverses have been lastly developed (important monographs were written by Rao and Mitra, Ben-Israel and Greville, Campbell and Meyer, Wang, Wei and Qiao). Generalized inverses cover a wide range of mathematical areas: matrix theory, operator theory, C∗-algebras or rings. Recent studies focus on: numerical computation, reverse order law, perturbation theory, partial orders, etc. Numerous applications include areas such as: statistics, differential equations, numerical analysis, Markov chains, cryptography, control theory, coding theory, incomplete data recovery and robotics.

11:00–11:25 The group inverse of additively modified matrices
Nieves Castro González, Universidad Politécnica de Madrid, Spain

11:25–11:50 The Moore-Penrose inverse of a linear combination of commuting generalized and hypergeneralized projectors
Dragana S. Cvetkovíc-Ilíc, University of Nis, Serbia

11:50–12:15 Generalized inverses of operators on Hilbert C∗-modules
Dragan S. Djordjevic, University of Nis, Serbia

12:15–12:40 Some results on the reverse order law
Dijana Mosic, University of Nis, Serbia

Wednesday, June 20

MS 39. Challenges for the solution and preconditioning of multiple linear systems -Part I of II
Organizer: Eric de Sturler
Virginia Tech, USA
Organizer: Daniel B. Szyld
Temple University, USA

This minisymposium presents challenging problems and new methods for the solution and preconditioning of multiple linear systems. These include parameterized linear systems, systems with multiple shifts, slowly varying systems, and variants from a range of applications, such as acoustics, model reduction, electronic structure, time-dependent problems, and linear and nonlinear eigenvalue problems. These methods include tensor Krylov subspace methods, recycling Krylov subspaces and other subspaces, and techniques for recycling preconditioners, including AMG and other multilevel preconditioners.

11:00–11:25 Preconditioners for sequences of shifted linear systems
Martin B. van Gijzen, Delft University of Technology, the Netherlands; Daniel B. Szyld, Temple University, USA

11:25–11:50 Solving sequences of linear systems with application to model reduction
Kapil Ahuja, Max Planck Institute for Dynamics of Complex Technical Systems, Germany; Eric de Sturler, Virginia Tech, USA; Serkan Gugercin, Virginia Tech, USA; Peter Benner, Max Planck Institute for Dynamics of Complex Technical Systems, Germany

11:50–12:15 Krylov subspace recycling for families of shifted linear systems
Kirk M. Soodhalter, Temple University, USA; Daniel B. Szyld, Temple University, USA; Fei Xue, Temple University, USA

12:15–12:40 Krylov subspace recycling for faster model reduction algorithms
Peter Benner, Max Planck Institute for Dynamics of Complex Technical Systems, Germany; Lihong Feng, Max Planck Institute for Dynamics of Complex Technical Systems, Germany

Wednesday, June 20

MS 40. Different perspectives on conditioning and numerical stability -Part I of II
Organizer: Froilán M. Dopico
Universidad Carlos III, Spain
Organizer: Ilse C.F. Ipsen
North Carolina State University, USA

The purpose of the minisymposium is two-fold: First, to call attention to the continued importance of conditioning and numerical stability, which have been expanding far beyond the traditional direct methods for dense matrices. Second to stimulate awareness and cross fertilization of concepts and techniques among different areas. To capture the wide variety of emerging directions, the minisymposium will consist of two sessions. Different perspectives on conditioning and numerical stability will be highlighted in the following specific contexts: functions of matrices, tensors, finite elements for PDEs, fast algorithms for rank structured matrices, Krylov methods for eigenvalues, orthogonalization methods, randomized algorithms, and high relative accuracy methods.

11:00–11:25 Highly accurate numerical linear algebra via rank revealing decompositions
Froilán M. Dopico, Univ. Carlos III, Spain

11:25–11:50 Stability of numerical algorithms with quasiseparable matrices
Pavel Zhlobich, Univ. of Edinburgh, UK; Froilán M. Dopico, Univ. Carlos III, Spain; Vadim Olshevsky, Univ. of Connecticut, USA

11:50–12:15 Gram-Schmidt orthogonalization with standard and non-standard inner product: rounding error analysis
Miroslav Rozlozník, Academy of Sciences, Czech Rep.; Jirí Kopal, Tech. Univ. of Liberec, Czech Rep.; Alicja Smoktunowicz, Warsaw Univ. of Tech., Poland; Miroslav Tuma, Academy of Sciences, Czech Rep

12:15–12:40 Backward stability of iterations for computing the polar decomposition
Nicholas J. Higham, Univ. of Manchester, UK; Yuji Nakatsukasa, Univ. of Manchester, UK

Wednesday, June 20

MS 41. Recent advances in model reduction -Part I of II
Organizer: Athanasios C. Antoulas
Rice University, USA
Organizer: Serkan Gugercin
Virginia Polytechnic Institute, USA

Direct numerical simulation of dynamical systems has been one of very few strategies when objectives include accurate prediction or control of complex physical phenomena. However, large-scale simulations often threaten untenable demands on computational resources, and in this way provide the main motivation for model reduction: Produce a simpler reduced-order dynamical system that approximates the input-output map of the original system accurately, yet cheaply. This mini-symposium will highlight the recent advances in model reduction from data-driven model reduction techniques to optimal model reduction techniques in simulation and control referring to applications that range from fluid flow to circuit simulation.

11:00–11:25 The Loewner framework in data-driven model reduction
Athanasios C. Antoulas, Rice University

11:25–11:50 Robust computational approaches to H2-optimal model reduction
Christoper A. Beattie, Virginia Polytechnic Institute, USA; Serkan Gugercin, Virginia Polytechnic Institute, USA

11:50–12:15 Reduced order modeling via frames
Volker Mehrmann, TU Berlin; Sadegh Jokar, TU Berlin; Sarosh Quraischi, TU Berlin

12:15–12:40 Semidefinite Hankel-type model reduction based on frequency response matching
Aivar Sootla, Lund University; Anders Rantzer, Lund University; Kin Cheong Sou, KTH

Wednesday, June 20

MS 42. Structured solution of nonlinear matrix equations and applications -Part I of II
Organizer: Eric King-wah Chu
Monash University, Australia
Organizer: Wen-Wei Lin
National Chiao Tung University, Taiwan

Nonlinear matrix equations, such as X + BX−1A + C =0, AX2 + BX + C =0 and AX + XD − XCX + B =0, arise in many applications, such as vibration analysis, optimal control, queueing systems, nano research and economic dynamics. The exploitation of specific symmetry and structures in these equations is vital in their numerical solution, especially for large-scale problems. Much have been achieved recently, using Newton’s iteration, cyclic reduction, doubling and other methods. The minisymposium will exhibit some of these advances and achievements, as well as explore some future directions of research and applications.

11:00–11:25 Structured solution of large-scale algebraic Riccati and nonlinear matrix equations
Eric King-wah Chu, Monash University; Tiexiang Li, Southeast University; Wen-Wei Lin, National Chiao Tung University; Peter Chang-Yi Weng, Monash University

11:25–11:50 Accurate solutions of nonlinear matrix equations in queueing models
Qiang Ye, University of Kentucky, U.S.

11:50–12:15 A numerical approach for solving nonlinear matrix equations in economic dynamics
Matthew M. Lin, National Chung Cheng University; Moody T. Chu, North Carolina State University; Chun-Hung Kuo, North Carolina State University

12:15–12:40 A structure-preserving doubling algorithm for quadratic eigenvalue problems arising from time-delay systems
Tiexiang Li, Southeast University; Eric King-wah Chu, Monash University; Wen-Wei Lin, National Chiao Tung University

Wednesday, June

MS 43. Challenges for the solution and preconditioning of multiple linear systems -Part II of II
Organizer: Eric de Sturler
Virginia Tech, USA
Organizer: Daniel B. Szyld
Temple University, USA

This minisymposium presents challenging problems and new methods for the solution and preconditioning of multiple linear systems. These include parameterized linear systems, systems with multiple shifts, slowly varying systems, and variants from a range of applications, such as acoustics, model reduction, electronic structure, time-dependent problems, and linear and nonlinear eigenvalue problems. These methods include tensor Krylov subspace methods, recycling Krylov subspaces and other subspaces, and techniques for recycling preconditioners, including AMG and other multilevel preconditioners.

15:00–15:25 Low-rank techniques for parameter-dependent linear systems and eigenvalue problems
Christine Tobler, EPF Lausanne, Switzerland; Daniel Kressner, EPF Lausanne, Switzerland

15:25–15:50 Recycling Krylov subspace information in sequences of linear systems
Nemanja Bozovic, Bergische Universität Wuppertal

15:50–16:15 Efficiently updating preconditioners in quantum Monte Carlo simulations
Arielle Grim McNally, Virginia Tech, USA; Eric de Sturler, Virginia Tech, USA; Kapil Ahuja, Max Planck Institute for Dynamics of Complex Technical Systems, Germany; Li Ming, Virginia Tech, USA

16:15–16:40 A domain decomposition preconditioned recycling GMRES for stochastic parabolic PDE
Xiao-Chuan Cai, University of Colorado at Boulder, USA

Wednesday, June 20

MS 44. Different perspectives on conditioning and numerical stability -Part II of II
Organizer: Froilán M. Dopico
Universidad Carlos III de Madrid, Spain
Organizer: Ilse C.F. Ipsen
North Carolina State University, USA

The purpose of the minisymposium is two-fold: First, to call attention to the continued importance of conditioning and numerical stability, which have been expanding far beyond the traditional direct methods for dense matrices. Second to stimulate awareness and cross fertilization of concepts and techniques among different areas. To capture the wide variety of emerging directions, the minisymposium will consist of two sessions. Different perspectives on conditioning and numerical stability will be highlighted in the following specific contexts: functions of matrices, tensors, finite elements for PDEs, fast algorithms for rank structured matrices, Krylov methods for eigenvalues, orthogonalization methods, randomized algorithms, and high relative accuracy methods.

15:00–15:25 Accuracy and sensitivity of Monte Carlo matrix multiplication algorithms
John T. Holodnak, North Carolina State University, USA; Ilse C. F. Ipsen, North Carolina State University, USA

15:25–15:50 Hyperdeterminant and the condition number of a multilinear system
Lek-Heng Lim, University of Chicago, USA

15:50–16:15 Condition numbers and backward errors in functional setting
Agnieszka Miedlar, Technical University of Berlin, Germany; Mario Arioli, STFC Rutherford Appleton Laboratory, UK

16:15–16:40 Orthogonality and stability in large-sparse-matrix iterative algorithms
Chris Paige, McGill University, Canada; Wolfgang Wülling, W2 Actuarial & Math Services Ltd., Germany

MS 45. Recent advances in model reduction -Part II of II
Organizer: Athanasios C. Antoulas
Rice University, USA
Organizer: Serkan Gugercin
Virginia Polytechnic Institute and State University, USA

Direct numerical simulation of dynamical systems has been one of very few strategies when objectives include accurate prediction or control of complex physical phenomena. However, large-scale simulations often threaten untenable demands on computational resources, and in this way provide the main motivation for model reduction: Produce a simpler reduced-order dynamical system that approximates the input-output map of the original system accurately, yet cheaply. This mini-symposium will highlight the recent advances in model reduction from data-driven model reduction techniques to optimal model reduction techniques in simulation and control referring to applications that range from fluid flow to circuit simulation.

15:00–15:25 Automating DEIM for nonlinear model reduction
Danny Sorensen, Rice University

15:25–15:50 Model reduction for optimal control problems in field-flow fractionation
Tatjana Stykel, Universität Augsburg

15:50–16:15 Numerical implementation of the iterative rational Krylov algorithm for optimal H2 model order reduction
Zlatko Drmac, University of Zagreb; Christopher A. Beattie, Virginia Polytechnic Institute; Serkan Gugercin, Virginia Polytechnic Institute

16:15–16:40 Low rank deflative/iterative solutions of Luré equations
Timo Reis, Universität Hamburg; Federico Poloni, Technische Universität Berlin

Wednesday, June 20

MS 46. Structured solution of nonlinear matrix equations and applications -Part II of II
Organizer: Eric King-wah Chu
Monash University, Australia
Organizer: Wen-Wei Lin
National Chiao Tung University, Taiwan

Nonlinear matrix equations, such as X + BX^{-1}A + C =0, AX^{2} + BX + C =0 and AX + XD − XCX + B =0, arise in many applications, such as vibration analysis, optimal control, queueing systems, nano research and economic dynamics. The exploitation of specific symmetry and structures in these equations is vital in their numerical solution, especially for large-scale problems. Much have been achieved recently, using Newton’s iteration, cyclic reduction, doubling and other methods. The minisymposium will exhibit some of these advances and achievements, as well as explore some future directions of research and applications.

15:00–15:25 Inertia and rank characterizations of the expressions A − BXB^{∗} − CYC*{∗} and A − BXC^{∗} ± CX^{∗}B^{∗}
Delin Chu, National University of Singapore

15:25–15:50 Structure-preserving Arnoldi-type algorithm for solving eigenvalue problems in leaky surface wave propagation
Tsung-Ming Huang, National Taiwan Normal University; Wen-Wei Lin, National Chiao Tung University; Chin-Tien Wu, National Chiao Tung University

15:50–16:15 Structure-preserving curve for symplectic pairs
Yueh-Cheng Kuo, National University of Kaohsiung; Shih-Feng Shieh, National Taiwan Normal University

16:15–16:40 A doubling algorithm with shift for solving a nonsymmetric algebraic Riccati equation
Chun-Yueh Chiang, National Formosa University; Matthew M. Lin, National Chung Cheng University

Wednesday, June 20

MS 47. Generalized inverses and applications -Part II of II
Organizer: Dragana S. Cvetkovic-Ilic
University of Nis, Serbia
Organizer: Néstor Thome
Universitat Politècnica de València, Spain
Organizer: Yimin Wei
Fudan University, P.R. China

Generalized inverses was first introduced on operators (Fredholm (1903), Hilbert (1904)) and later on matrices (Moore (1920), Penrose (1955)). The most important fact was its conection with least-squares method. Theory, applications and computational methods of generalized inverses have been lastly developed (important monographs were written by Rao and Mitra, Ben-Israel and Greville, Campbell and Meyer, Wang, Wei and Qiao). Generalized inverses cover a wide range of mathematical areas: matrix theory, operator theory, C∗-algebras or rings. Recent studies focus on: numerical computation, reverse order law, perturbation theory, partial orders, etc. Numerous applications include areas such as: statistics, differential equations, numerical analysis, Markov chains, cryptography, control theory, coding theory, incomplete data recovery and robotics.

15:00–15:25 On a partial order defined on certain matrices
Néstor Thome, Universitat Politècnica de València, Spain; Araceli Hernández, Marina Lattanzi and Fabián Urquiza, Universidad Nacional de La Pampa, Argentina

15:25–15:50 Generalized inverses and path products
Pedro Patrício, Universidade do Minho, Portugal; R. Hartwig, N.C.S.U. Raleigh, USA

15:50–16:15 On structured condition numbers for a linear functional of Tikhonov regularized solution
Yimin Wei, Fudan University, P.R. China; Huaian Diao, Northeast Normal University, P.R. China

16:15–16:40 Explicit characterization of the Drazin index
Qingxiang Xu, Shanghai Normal University, P.R. China

Wednesday, June 20

MS 48. Parallelization of efficient algorithms
Organizer: Matthias Bolten
University of Wuppertal, Germany
Organizer: Stefan Kunis
University of Osnabrueck, Germany

Effective discretizations and efficient algorithms are necessary for modelling complex and high dimensional problems in various applications. Algorithms, scaling up to logarithmic factors linear in the problem size, typically reuse intermediate results several times and thus have a strong data dependence. We concentrate on best practice examples on modern computing architectures and aim to conclude with general guidelines for the parallelization of efficient algorithms.

15:00–15:25 A highly scalable error-controlled fast multipole method
Ivo Kabadshow, Forschungszentrum Jülich, Supercomputing Centre

15:25–15:50 A parallel fast Coulomb solver based on nonequispaced Fourier transforms
Michael Pippig, Chemnitz University of Technology

15:50–16:15 Generalized fast Fourier transforms via CUDA
Susanne Kunis, University of Osnabrück

16:15–16:40 Efficient regularization and parallelization for sparse grid regression
Dirk Pfluger, Technische Universität München

Wednesday, June 20

MS 49. Analysis and computation on matrix manifold
Organizer: Bruno Iannazzo
Università di Perugia, Italy

The definition and analysis of manifold structures on certain sets of matrices and tensors have proved to be a fruitful topic in pure and applied linear algebra, opening the possibility to find the right definition of matrix geometric mean, to give new understandings and methods for classical problems as the eigencomputation or the solution of matrix equations. The power of the manifold approach has led to applications which range from elasticity to medical imaging and signal processing. Current lines of research are the theoretical analysis of matrix and tensor manifolds and the design of algorithms which exploit the manifold structures.

15:00–15:25 Best low multilinear rank approximation of symmetric tensors by Jacobi rotations
Pierre-Antoine Absil, Université catholique de Louvain; Mariya Ishteva, Georgia Institute of Technology; Paul Van Dooren, Université catholique de Louvain

15:25–15:50 Differential geometry for tensors with fixed hierarchical Tucker rank
Bart Vandereycken École Polytechnique Fédérale de Lausanne; André Uschmajew, Technische Universität (TU) Berlin

15:50–16:15 Deterministic approaches to the Karcher mean of positive definite matrices
Yongdo Lim, Kyungpook National University

16:15–16:40 The Karcher mean: first and second order optimization techniques on matrix manifolds
Ben Jeuris, Katholieke Universiteit Leuven; Raf Vandebril, Katholieke Universiteit Leuven; Bart Vandereycken, Ecole Polytechnique Fédérale de Lausanne

Wednesday, June 20

MS 50. Advanced methods for large eigenvalue problems and their applications
Organizer: Tetsuya Sakurai
University of Tsukuba, Japan
Organizer: Nahid Emad
University of Versailles, France

The massive increase of the number of processors into high performance computers and the number of cores into these processors make more complex the new architectures or those emerging. There is a growing need for efficient numerical methods to take full advantage of the ability of these supercomputers in various computational fields. The minisymposium focuses on advanced methods for large-scale eigenvalue problems that arise in scientific and industrial areas. Emphasis are placed on the new numerical approaches to exploit the massive and multi-level parallelism of these supercomputers.

15:00–15:25 DQDS with aggressive early deflation for computing singular values
Kensuke Aishima, University of Tokyo, Japan; Yuji Nakatsukasa, University of Manchester, UK; Ichitaro Yamazaki, University of Tennessee, USA

15:25–15:50 A scalable parallel method for large scale nonlinear eigenvalue problems
Kazuma Yamamoto, University of Tsukuba, Japan; Tetsuya Sakurai, University of Tsukuba, Japan

15:50–16:15 Application of the Sakurai-Sugiura method in the field of density functional theory on highly parallel systems
Georg Huhs, Barcelona Supercomputing Center, Spain

16:15–16:40 MERAM for neutron physics applications using YML environment on post petascale heterogeneous architecture
Christophe Calvin, Gif-Sur-Yvette Cedex France; Nahid Emad, University of Versailles, France; Serge Petiton, Lille University/INRIA France; Jérôme Dubois, CEA Saclay, France; Makarem Dandouna, University of Versailles, France

Thursday, June 21

MS 51. Accurate and verified numerical computations for numerical linear algebra
Organizer: Takeshi Ogita
Tokyo Woman’s Christian University, Japan
Organizer: Siegfried M. Rump
Hamburg University of Technology, Germany

This minisymposium is devoted to accurate and verified computations for numerical linear algebra. Such computations have become increasingly important in wide range of science and engineering, especially when requiring high reliability in solving ill-conditioned problems. Although there are many useful numerical algorithms and softwares for obtaining reliable results, they are still not widely known nor used in practical applications. The main objective of the minisymposium is to discuss several recent topics on fast, accurate and verified numerical algorithms and softwares for linear systems, eigenvalue problems, floating-point arithmetic and multiple precision arithmetic.

11:00–11:25 Product decomposition and its applications
Naoya Yamanaka, Waseda University; Shiníchi Oishi, Waseda University

11:25–11:50 The MPACK: multiple precision version of BLAS and LAPACK
Maho Nakata, RIKEN

11:50–12:15 On eigenvalue computations of nonderogatory matrices
Aurél Galántai, Óbuda University

12:15–12:40 Verified solutions of sparse linear systems
Takeshi Ogita, Tokyo Woman’s Christian University

Thursday, June 21

MS 52. Numerical linear algebra libraries for high end computing -Part I of II
Organizer: L. A. Drummond
Berkeley, US
Organizer: Nahid Emad
University of Versailles, France
Organizer: Jose E. Roman
Universitat Politècnica de València, Spain

The increase in computational power and the diversity of hardware have prompted the inception of linear algebra algorithms that can exploit multiple levels of concurrency to achieve larger orders of computational and problem solving scalability. Here we review the state of the art numerical linear algebra kernels for HPC. We focus on new algorithmic developments, parameterization and optimization, as well as software implementations and their deployment in emerging computer systems. Also relevant to this mini-symposium are the software reusability and library interoperability efforts to jumpstart the academic and industrial software development.

11:00–11:25 Large-scale eigenvalue computation with PETSc and YML
Makarem Dandouna, Univ. of Versailles, France; Nahid Emad, Univ. of Versailles, France; L.A. (Tony) Drummond, Lawrence Berkeley National Laboratory, USA

11:25–11:50 Sparse matrix-matrix operations in PETSc
Hong Zhang, Illinois Institute of Technology, USA; Barry Smith and PETSc Team, Argonne National Laboratory, USA

11:50–12:15 Hierarchical QR factorization algorithms for multi-core cluster systems
Julien Langou, Univ. of Colorado Denver, USA; Jack Dongarra and Mathieu Faverge, Univ. of Tennessee, USA; Thomas Herault, Univ. Paris-Sud, France; Yves Robert, Ecole Normale Supérieure de Lyon, France

12:15–12:40 Towards robust numerical algorithms for exascale simulation
Emmanuel Agullo, INRIA Bordeaux Sud-Ouest, France; Luc Giraud, Abdou Guermouche, Jean Roman and Mawussi Zounon, INRIA, France

Thursday, June 21

MS 53. Efficient preconditioners for real world applications -Part I of II
Organizer: Massimiliano Ferronato
University of Padova, Italy
Organizer: Carlo Janna
University of Padova, Italy
Organizer: Luca Bergamaschi
University of Padova, Italy

The efficient solution to sparse linear systems is quite a common issue in several real world applications and often represents the main memory-and time-consuming task in a computer simulation. In many areas of engineering and scientific computing, the solution to large sparse systems relies on iterative methods based on Krylov subspaces. Nonetheless, to become really efficient Krylov solvers need appropriate preconditioning to achieve convergence in a reasonable number of iterations. Unfortunately, it is widely recognized that an optimal general-purpose preconditioner is unlikely to exist. In this minisymposium, we want to present novel scalar and parallel preconditioning techniques specifically designed for real world applications.

11:00–11:25 A parallel factored preconditioner for non-symmetric linear systems
Carlo Janna, Univ. of Padova, Italy; Massimiliano Ferronato and Giorgio Pini, Univ. of Padova, Italy

11:25–11:50 Preconditioning for linear least-squares problems
Miroslav Tuma, Academy of Sciences of the Czech Republic, Czech Republic; Rafael Bru, José Mas and José Marín, Univ. Politècnica de València, Spain

11:50–12:15 Robust and parallel preconditioners for mechanical problems
Kees Vuik, Technology Univ. of Delft, The Netherlands; Tom Jönsthövel and Martin van Gijzen, Technology Univ. of Delft, The Netherlands

12:15–12:40 Block factorized forms of SPAI
Thomas Huckle, Technische Univ. München, Germany; Matous Sedlacek, Technische Univ. München, Germany

Thursday, June 21

MS 54. Solving ill-posed systems via signal-processing techniques-Part I of II
Organizer: Stephen Becker
LJLL, Paris-6/CNRS, France
Organizer: Dirk Lorenz
TU Braunschweig Germany

In compressed sensing (CS) and sparse recovery problems, one seeks to solve an underdetermined or ill-posed equation by exploiting prior knowledge such as sparsity. These signal-processing problems have benefited from established results on optimization and greedy methods, but they have also introduced many novel results which are widely-applicable even outside the target applications. This minisymposium focuses on the computational, algorithmical and numerical aspects of these techniques. We bring together researchers who work on a wide variety of approaches, e.g. subgradient methods, semismooth methods or proximal methods.

11:00–11:25 Sequential updates for L1 minimization: sparse Kalman filtering, reweighted L1, and more
Justin Romberg, Georgia Tech; M. Salman Asif, Georgia Tech.

11:25–11:50 Solving basis pursuit: infeasible-point subgradient algorithm, computational comparison, and improvements
Andreas Tillmann, Technische Universität Braunschweig; Dirk Lorenz, Technische Universität Braunschweig; Marc Pfetsch, Technische Universität Braunschweig

11:50–12:15 Semismooth Newton methods with multi-dimensional filter globalization for l_{1} optimization
Andre Milzarek, Technische Universität Muenchen; Michael Ulbrich, Technische Universität Muenchen

12:15–12:40 Improved first-order methods: how to handle constraints, non-smoothness, and slow convergence
Stephen Becker, Paris-6/CNRS; Jalal Fadili, CNRS-ENSICAEN-Université de Caen; Emmanuel Candès, Stanford University; Michael Grant, CVX Research

Thursday, June 21

MS 55. Max-algebra -Part I of II
Organizer: Hans Schneider
Univ. of Wisconsin, USA
Organizer: Peter Butkovic
Univ. of Birmingham, UK

Max-algebra (also known as tropical algebra) and its generalization to idempotent algebra are rapidly evolving areas of algebra, designed to solve problems which are non-linear in classical algebra but become linear in max-algebra. Such problems may be found in mathematics, operational research, computer science and engineering. While 25 years ago there were only isolated researchers in this area, since 1995 we have seen remarkable expansion following a number of advances and applications in areas as diverse as algebraic geometry, phylogenetics and railway scheduling. This is the first of the two mini-symposia that provide eight state-of-the-art research presentations.

11:00–11:25 Tropical bounds for the eigenvalues of structured matrices
Marianne Akian, INRIA Saclay-IIle-de-France; Stephane Gaubert, INRIA Saclay–IIle-de-France; Meisam Sharify, INRIA Saclay–IIle-de-France

11:25–11:50 Sensitivity in extremal systems of linear equations and inequalities
Karel Zimmermann, Charles University Prague; Martin Gavalec, University of Hradec Králové

11:50–12:15 Multiplicative structure of tropical matrices
Mark Kambites, University of Manchester

12:15–12:40 Transience bounds for matrix powers in max algebra
Sergeı Sergeev, University of Birmingham

Thursday, June 21

MS 56. Eigenvalue perturbations and pseudospectra -Part I of II
Organizer: Daniel Kressner
EPF Lausanne, Switzlerland
Organizer: Julio Moro
Universidad Carlos III de Madrid, Spain

The behavior of matrix eigenvalues under perturbations is a classical topic in (numerical) linear algebra and has been under continuous investigation for several decades. The aim of this minisymposium is to highlight some recent exciting developments in this area. For example, in applications from systems and control theory it is often more realistic to impose a certain structure on the perturbations. Significant progress has been made in analyzing and computing the corresponding structured eigenvalue condition numbers and pseudospectra. For both, structured and unstructured pseudospectra, a more refined understanding of analytical properties has led to improved algorithms for computing pseudospectral quantities, such as the pseudospectral abscissa or the H∞ norm. Finally, the localization of Ritz value is an impressive recent example for the use of pseudospectra in understanding the convergence of Krylov subspace methods.

11:00–11:25 Inclusion theorems for pseudospectra of block triangular matrices
Michael Karow, TU Berlin, Germany

11:25–11:50 Conjectures on pseudospectra of matrices
Juan-Miguel Gracia, The Univ. of the Basque Country, Spain

11:50–12:15 Sensitivity of eigenvalues of an unsymmetric tridiagonal matrix
Carla Ferreira, Univ. of Minho, Portugal; Beresford Parlett, Univ. of California, USA; Froilán Dopico, Univ. Carlos III de Madrid, Spain

12:15–12:40 First order structured perturbation theory for eigenvalues of skew-adjoint matrices
Julio Moro, Univ. Carlos III de Madrid, Spain; María J. Peláez, Univ. Cat. del Norte, Chile

Thursday, June 21

MS 57. Numerical linear algebra and optimization in imaging applications -Part I of II
Organizer: Julianne Chung
University of Texas at Arlington, USA
Organizer: Roummel Marcia
University of California, USA

Image processing is widely used in many of today’s practical applications, from medicine and astronomy to ecology and security. Oftentimes, the underlying problem in these applications is an inverse problem, posing many challenges such as scale and ill-posedness. While many numerical methods have been developed to address these challenges, recent advances in imaging techniques require faster and more robust methods. Numerical linear algebra and numerical optimization continue to play a vital role in the development of these algorithms, and this two-session minisymposium will highlight the latest contributions. A diversity of problems, algorithms, and applications will be addressed.

11:00–11:25 Some numerical linear algebra and optimization problems in spectral imaging
Robert Plemmons, Wake Forest University; J. Erway, Wake Forest University; N. Gillis, University of Waterloo; X. Hu, Wake Forest University; M. Ng, Hong Kong Baptist University; P. Pauca, Wake Forest University; S. Prasad, University of New Mexico; J. Zhang, Wake Forest University; Q. Zhang, Wake Forest University

11:25–11:50 Image restoration via constrained optimization: an approach using feasible direction methods
Germana Landi, University of Bologna

11:50–12:15 On the solution of linear systems in Newton-type methods for image reconstruction
Elena Piccolomini, University of Bologna

12:15–12:40 Alternating direction optimization for convex inverse problems with application to imaging and hyperspectral unmixing
Jose Bioucas-Dias, Technical University of Lisbon

Thursday, June 21

MS 58. Parametric eigenvalue problems -Part I of II
Organizer: K. Meerbergen
K.U. Leuven, Belgium
Organizer: W. Michiels
K.U. Leuven, Belgium
Organizer: C. Lecomte
University of Southampton, University Road, Highfield, UK

In applications, matrices, and thus also their eigenvalues, depend on physical parameters. The eigenvalues are usually continuous functions of the parameters, a property, which is used by, e.g., numerical methods for determining pseudospectra, the distance to instability, Hopf bifurcations, etc. In this minisymposium, we bring together a collection of talks with very different viewpoints, methods and applications, related to parametric eigenvalue problems.

11:00–11:25 Computing double eigenvalues via the two-parameter eigenvalue problem
Bor Plestenjak, University of Ljubljana, Slovenia

11:25–11:50 Lyapunov inverse iteration for identifying Hopf bifurcations in models of incompressible flow
Alastair Spence, University of Bath, UK; Howard Elman, University of Maryland, USA; Karl Meerbergen, K.U.Leuven, Belgium; Minghao Wu, University of Maryland, USA

11:50–12:15 A quadratically convergent algorithm for matrix distance problems
Melina Freitag, University of Bath, UK; Alastair Spence, University of Bath, UK

12:15–12:40 A real Jacobi-Davidson algorithm for the 2-real-parameter eigenvalue problem
Christian Schröder, TU Berlin, Germany

Thursday, June 21

MS 59. Structured matrix computations -Part I of II
Organizer: Jianlin Xia
Purdue University, US
Organizer: Xiaoye S. Li
Lawrence Berkeley National Laboratory, USA

Structured matrices have been widely used to solve large matrix problems, PDEs, integral equations, etc. In recent developments, rank structured methods with high efficiency, stability, and scalability are proposed, and are suitable for large-scale scientific computing. In this minisympisium, a variety of matrix structures are discussed, including hierarchical, semiseparable, and quasiseparable matrices. Their applications to large control, imaging, geophysics, and engineering problems are illustrated. New research directions for structured matrices are discussed, such as innovative structured factorization, preconditioning, and eigensolution techniques.

11:00–11:25 Factorization of H2-matrices
Steffen Börm, Institut für Informatik, Christian-Albrechts-Universität zu Kiel

11:25–11:50 The polynomial root finding problems and quasiseparable representations of unitary matrices
Yuli Eidelman, Tel-Aviv University, Israel

11:50–12:15 A fast direct solver for structured matrices arising from non-oscillatory integral equations
Kenneth L. Ho, New York University, USA; Leslie Greengard, New York University

12:15–12:40 Multivariate orthogonal polynomials and inverse eigenvalue problems
Matthias Humet, University of Leuven; Marc Van Barel, University of Leuven

Thursday, June 21

MS 60. Numerical linear algebra libraries for high end computing -Part II of II
Organizer: L. A. Drummond
Berkeley, US
Organizer: Nahid Emad
University of Versailles, France
Organizer: Jose E. Roman
Universitat Politècnica de València, Spain

The increase in computational power and the diversity of hardware have prompted the inception of linear algebra algorithms that can exploit multiple levels of concurrency to achieve larger orders of computational and problem solving scalability. Here we review the state of the art numerical linear algebra kernels for HPC. We focus on new algorithmic developments, parameterization and optimization, as well as software implementations and their deployment in emerging computer systems. Also relevant to this mini-symposium are the software reusability and library interoperability efforts to jumpstart the academic and industrial software development.

15:00–15:25 Thick-restart Lanczos methods for symmetric-indefinite generalized eigenproblems in SLEPc
Jose E. Roman, Universitat Politècnica de València, Spain; Carmen Campos, Universitat Politècnica de València, Spain

15:25–15:50 Parametric approach to smart-tuning and auto-tuning of the DOE ACTS collection
L. A. (Tony) Drummond, Lawrence Berkeley National Laboratory, USA; O A. Marques, Lawrence Berkeley National Laboratory, USA

15:50–16:15 Trilinos: foundational libraries that enable next-generation computing
Heidi Thornquist, Sandia National Laboratory, USA; The Trilinos Development Team, Sandia National Laboratory, USA

16:15–16:40 Rethinking distributed dense Linear Algebra
Jack Poulson, The University of Texas at Austin, USA

Thursday, June 21

MS 61. Efficient preconditioners for real world applications -Part II of II
Organizer: Massimiliano Ferronato
University of Padova, Italy
Organizer: Carlo Janna
University of Padova, Italy
Organizer: Luca Bergamaschi
University of Padova, Italy

The efficient solution to sparse linear systems is quite a common issue in several real world applications and often represents the main memory-and time-consuming task in a computer simulation. In many areas of engineering and scientific computing, the solution to large sparse systems relies on iterative methods based on Krylov subspaces. Nonetheless, to become really efficient Krylov solvers need appropriate preconditioning to achieve convergence in a reasonable number of iterations. Unfortunately, it is widely recognized that an optimal general-purpose preconditioner is unlikely to exist. In this minisymposium, we want to present novel scalar and parallel preconditioning techniques specifically designed for real world applications.

15:00–15:25 Relaxed mixed constraint preconditioners for ill-conditioned symmetric saddle point linear systems
Luca Bergamaschi, Univ. of Padova, Italy; Ángeles Martínez, Univ. of Padova, Italy

15:25–15:50 Chebychev acceleration of iterative refinement
Jennifer Scott, Science and Technology Faculties Council, UK; Mario Arioli, Science and Technology Faculties Council, UK

15:50–16:15 Parallel deflated GMRES with the Newton basis
Désiré Nuentsa Wakam, INRIA, Bordeaux, France; Jocelyne Erhel, INRIA, Rennes, France

16:15–16:40 Rank-k updates of incomplete Sherman-Morrison preconditioners
José Marín, Universidad Politécnica de Valencia, Spain; Juana Cerdán and José Mas, Universitat Politècnica de València, Spain

Thursday, June 21

MS 62. Solving ill-posed systems via signal-processing techniques-Part II of II
Organizer: Stephen Becker
LJLL, Paris-6/CNRS, France
Organizer: Dirk Lorenz
TU Braunschweig, Germany

In compressed sensing (CS) and sparse recovery problems, one seeks to solve an underdetermined or ill-posed equation by exploiting prior knowledge such as sparsity. These signal-processing problems have benefited from established results on optimization and greedy methods, but they have also introduced many novel results which are widely-applicable even outside the target applications. This minisymposium focuses on the computational, algorithmical and numerical aspects of these techniques. We bring together researchers who work on a wide variety of approaches, e.g. subgradient methods, semismooth methods or proximal methods.

15:00–15:25 Effects of prox parameter selection strategies in exact and inexact first-order methods for compressed sensing and other composite optimization problems
Katya Scheinberg, Lehigh University; Donald Goldfarb, Columbia University; Shiqian Ma, University of Minnesota

15:25–15:50 An adaptive inverse scale space method for compressed sensing
Martin Benning, University of Münster; Michael Möllerr, University of Münster; Pia Heins, University of Münster

15:50–16:15 CGSO for convex problems with polyhedral constraints
Sahar Karimi, University of Waterloo; Stephen Vavasis, University of Waterloo

16:15–16:40 Phase-retrieval using explicit low-rank matrix factorization
Ewout van den Berg, Stanford University; Emmanuel Candès, Stanford University

Thursday, June 21

MS 63. Max-algebra -Part II of II
Organizer: Hans Schneider
Univ. of Wisconsin, USA
Organizer: Peter Butkovic
Univ. of Birmingham, UK

Max-algebra (also known as tropical algebra) and its generalization to idempotent algebra are rapidly evolving areas of algebra, designed to solve problems which are non-linear in classical algebra but become linear in max-algebra. Such problems may be found in mathematics, operational research, computer science and engineering. While 25 years ago there were only isolated researchers in this area, since 1995 we have seen remarkable expansion following a number of advances and applications in areas as diverse as algebraic geometry, phylogenetics and railway scheduling. This is the second of the two mini-symposia that provide eight state-of-the-art research presentations.

15:00–15:25 Three-dimensional convex polyhedra tropically spanned by four points
María Jesús de la Puente, Universidad Complutense de Madrid, Spain; Adrián Jiménez, Universidad Complutense de Madrid, Spain

15:25–15:50 Algorithmic problems in tropical convexity
Xavier Allamigeon, INRIA Saclay–IIle-de-France and CMAP, Ecole Polytechnique; Stéphane Gaubert, INRIA Saclay–Ile-de-France and CMAP Ecole Polytechnique; Eric Goubault, CEA Saclay Nano-INNOV; Ricardo D. Katz, Universidad Nacional de Rosario

15:50–16:15 On the weak robustness of interval fuzzy matrices
Ján Plávka, Technical University Kosice; Martin Gavalec, University of Hradec Králové

16:15–16:40 Weakly stable matrices
Peter Butkovic, University of Birmingham

Thursday, June 21

MS 64. Eigenvalue perturbations and pseudospectra -Part II of II
Organizer: Daniel Kressner
EPF Lausanne, Switzlerland
Organizer: Julio Moro
Universidad Carlos III de Madrid, Spain

The behavior of matrix eigenvalues under perturbations is a classical topic in (numerical) linear algebra and has been under continuous investigation for several decades. The aim of this minisymposium is to highlight some recent exciting developments in this area. For example, in applications from systems and control theory it is often more realistic to impose a certain structure on the perturbations. Significant progress has been made in analyzing and computing the corresponding structured eigenvalue condition numbers and pseudospectra. For both, structured and unstructured pseudospectra, a more refined understanding of analytical properties has led to improved algorithms for computing pseudospectral quantities, such as the pseudospectral abscissa or the H∞ norm. Finally, the localization of Ritz value is an impressive recent example for the use of pseudospectra in understanding the convergence of Krylov subspace methods.

15:00–15:25 Ritz value localization for non-Hermitian matrices
Mark Embree, Rice University, USA; Russell Carden, Rice University

15:25–15:50 Optimization of eigenvalues of Hermitian matrix functions
Emre Mengi, Koç University, Turkey; Mustafa Kiliç, Koç University, Turkey; E. Alper Yıldırim, Koç University, Turkey

15:50–16:15 Algorithms for approximating the H∞ norm
Michael Overton, New York University, USA; Mert Gürbüzbalaban, New York University, USA; Nicola Guglielmi, University of L’Aquila, Italy

16:15–16:40 Reduced basis methods for computing pseudospectral quantities
Daniel Kressner, EPF Lausanne, Switzerland

Thursday, June 21

MS 65. Numerical linear algebra and optimization in imaging applications -Part II of II
Organizer: Julianne Chung
University of Texas at Arlington, USA
Organizer: Roummel Marcia
University of California, USA

Image processing is widely used in many of today’s practical applications, from medicine and astronomy to ecology and security. Oftentimes, the underlying problem in these applications is an inverse problem, posing many challenges such as scale and ill-posedness. While many numerical methods have been developed to address these challenges, recent advances in imaging techniques require faster and more robust methods. Numerical linear algebra and numerical optimization continue to play a vital role in the development of these algorithms, and this two-session minisymposium will highlight the latest contributions. A diversity of problems, algorithms, and applications will be addressed.

15:00–15:25 A recursion relation for solving L-BFGS systems with diagonal updates
Jennifer Erway, Wake Forest University; R. Marcia, University of California, USA

15:25–15:50 Wavefront gradients reconstruction using l^{1} − l^{p} models
Raymond Chan, The Chinese University of Hong Kong; X. Yuan, Hong Kong Baptist University; W. Zhang, Nanjing University

15:50–16:15 Edge-preserving image enhancement via blind deconvolution and upsampling operators
Antonio Marquina, University of Valencia, Spain; S. Osher, UCLA; S. Joshi, UCLA

16:15–16:40 A new hybrid-optimization method for large-scale, non-negative, full regularization
Marielba Rojas, Delft University of Technology, The Netherlands; J. Guerrero, Carabobo University, Venezuela; M. Raydan, Simón Bolívar University, Venezuela

Thursday, June 21

MS 66. Parametric eigenvalue problems -Part II of II
Organizer: K. Meerbergen
K.U. Leuven, Belgium
Organizer: W. Michiels
K.U. Leuven, Belgium
Organizer: C. Lecomte
University of Southampton, University Road, Highfield, UK

In applications, matrices, and thus also their eigenvalues, depend on physical parameters. The eigenvalues are usually continuous functions of the parameters, a property, which is used by, e.g., numerical methods for determining pseudospectra, the distance to instability, Hopf bifurcations, etc. In this minisymposium, we bring together a collection of talks with very different viewpoints, methods and applications, related to parametric eigenvalue problems.

15:00–15:25 A subspace optimization technique for the generalized minimal maximal eigenvalue problem
Jeroen De Vlieger, K.U.Leuven, Belgium; Karl Meerbergen, K.U.Leuven, Belgium

15:25–15:50 An iterative method for computing pseudospectral abscissa and stability radii for nonlinear eigenvalue problems
Wim Michiels, K.U.Leuven, Belgium; Nicola Guglielmi, Università dell’Aquila, Italy

15:50–16:15 Statistical pseudospectrum and eigenvalue robustness to rank-one disturbance
Christophe Lecomte, University of Southampton, UK; Maryam Ghandchi Tehrani, University of Southampton, UK

Thursday, June 21

MS 67. Structured matrix computations -Part II of II
Organizer: Jianlin Xia
Purdue University, US
Organizer: Xiaoye S. Li
Lawrence Berkeley National Laboratory, USA

Structured matrices have been widely used to solve large matrix problems, PDEs, integral equations, etc. In recent developments, rank structured methods with high efficiency, stability, and scalability are proposed, and are suitable for large-scale scientific computing. In this minisympisium, a variety of matrix structures are discussed, including hierarchical, semiseparable, and quasiseparable matrices. Their applications to large control, imaging, geophysics, and engineering problems are illustrated. New research directions for structured matrices are discussed, such as innovative structured factorization, preconditioning, and eigensolution techniques.

15:00–15:25 Randomized numerical matrix computations with applications
Victor Pan, University of New York, USA

15:25–15:50 Massively parallel structured direct solver for the equations describing time-harmonic seismic waves
Maarten V. de Hoop, Purdue University; Shen Wang, Purdue University; Jianlin Xia, Purdue University; Xiaoye S. Li, Lawrence Berkeley National Laboratory

15:50–16:15 Accelerating electronic structure calculation with pole expansion plus selected inversion method
Lin Lin and Chao Yang, Lawrence Berkeley National Laboratory

16:15–16:40 Randomized direct solvers
Jianlin Xia, Purdue University; Maarten V. de Hoop, Purdue University; Xiaoye S. Li, Lawrence Berkeley National Laboratory; Shen Wang, Purdue University

Friday, June 22

MS 68. Linear algebra for structured eigenvalue computations arising from (matrix) polynomials
Organizer: L. Gemignani
Univ. of Pisa, Italy
Organizer: R. Vandebril
KU Leuven, Belgium

Structured eigenvalue problems emerge in applications in science and engineering. Structure is induced by the original problem or introduced by linearization. The aim is to develop theory (canonical forms, perturbation theory) and numerical methods (linearizations and iterations) respecting structure and spectral properties, aiming at faster and more accurate solutions. A (generalized) companion matrix results from linearizing a (particular) polynomial root finding problem into a matrix eigenvalue problem. In this mini we will unite researchers interested in structured eigenvalue problems arising from (matrix) polynomials with a view to surveying the state-of-the-art and reporting on recent advances and challenges.

11:00–11:25 A QR algorithm with generator compression for structured eigenvalue computation
P. Boito, University of Limoges; Y. Eidelman, Tel-Aviv Univ.; L. Gemignani, Univ. of Pisa; I. Gohberg, Tel-Aviv Univ.

11:25–11:50 Quadratic realizability for structured matrix polynomials
D.S. Mackey, Western Michigan University; F. De Teáan and F.M. Dopico, Univ. Carlos III de Madrid; F. Tisseur, The University of Manchester

11:50–12:15 Fast computation of zeros of a polynomial
D.S. Watkins, Washington State Univ.; J.L. Aurentz, Washington State Univ.; R. Vandebril, KU Leuven

12:15–12:40 Eigenvector recovery of linearizations and the condition number of eigenvalues of matrix polynomials
F. De Terán, Univ. Carlos III de Madrid; M.I. Bueno, Univ. of California at Santa Barbara; F.M. Dopico, Univ. Carlos III de Madrid; D.S. Mackey, Western Michigan Univ.

Friday, June 22

MS 69. Advances in sparse matrix factorization
Organizer: A. Buttari
CNRS-IRIT, Toulouse, France
Organizer: S. Toledo
Tel-Aviv University, Israel

The ever increasing size of scientific problems and the fast pace at which computing architectures evolve force researchers to continuously update or rethink their algorithms and programming models. Sparse, direct solvers are no exception in this trend. This minisymposium will present recent advances, as well as the new and future challenges involving sparse, direct solvers. Specifically, it will focus on novel numerical methods for revealing mathematical properties of sparse matrices, algorithms for reducing the complexity and improving the efficiency of direct solvers as well as programming models for exploiting the computational power of modern, heterogeneous computers.

11:00–11:25 A Sparse inertia-revealing factorization
Alex Druinsky, Tel-Aviv University; S. Toledo, Tel-Aviv University

11:25–11:50 Multifrontal factorization on heterogeneous multicore systems
Bob Lucas, Univ. of Southern California; Roger Grimes, Livermore Software Technology Corp.; John Tran, Univ. of Southern California; Gene Wagenbreth, Univ. of Southern California

11:50–12:15 Towards an optimal parallel approximate sparse factorization algorithm using hierarchically semi-separable structures
Xiaoye S. Li, Lawrence Berkeley National Laboratory; Shen Wang, Purdue Univ.; Jianlin Xia, Purdue Univ.; Maarten V. de Hoop, Purdue Univ.

12:15–12:40 Improving multifrontal methods by means of low-rank approximation techniques
Clement Weisbecker, Univ. of Toulouse; Patrick Amestoy, Univ. of Toulouse; Cleve Ashcraft, LSTC, Livermore; Olivier Boiteau, EDF R&D, Clamart; Alfredo Buttari, CNRS-IRIT; Jean-Yves L’Excellent, INRIA-LIP(ENS Lyon)

Friday, June 22

MS 70. Accurate algorithms and applications
Organizer: Roberto Barrio
Universidad de Zaragoza, Spain
Organizer: Siegfried M. Rump
Hamburg University of Technology, Germany

At the present time, IEEE 64-bit floating-point arithmetic is sufficiently accurate for most scientific applications. However, for a rapidly growing body of important scientific computing applications, a higher level of numeric precision is required. Such calculations are facilitated by high-precision software packages. Another situation that requires new algorithms is the numerical solution in double precision of ill-posed problems in scientific applications. One alternative, related with some high-precision algorithms are the so called compensated algorithms. This minisymposium presents a survey of recent applications of these techniques and provides some analysis of their numerical requirements.

11:00–11:25 High precision and accurate algorithms in Physics and Mathematics
Roberto Barrio Universidad de Zaragoza, Spain; David H. Bailey, Lawrence Berkeley National Laboratory, USA; Jonathan M. Borwein, Univ. of Newcastle, Australia; Sergio Serrano, Univ. de Zaragoza, Spain

11:25–11:50 Accurate evaluation of 1D and 2D polynomials in Bernstein form
Hao Jiang, Universite of Pierre et Marie Curie, Paris, France; Roberto Barrio, Univ. de Zaragoza, Spain

11:50–12:15 Some issues related to double roundings
Jean-Michel Muller, CNRS, Université de Lyon, France; Erik Martin-Dorel, Université de Lyon, France; Guillaume Melquiond, INRIA, Université Paris Sud, France

12:15–12:40 Error bounds for floating-point summation and dot product
Siegfried M. Rump, Hamburg University of Technology, Germany and Waseda University, Japan

Friday, June 22

MS 71. Theoretical and applied aspects of graph Laplacians
Organizer: Shaun Fallat
University of Regina, CANADA
Organizer: Steve Kirkland
Hamilton Institute, National University of Ireland Maynooth, Ireland

The Laplacian matrix associated with a graph has its roots in the analysis of networks (beginning with Kirchoff) and has become a pillar for research in combinatorial matrix theory, informing new applications in both combinatorics and numerical linear algebra. Specifically, there has been a fruitful investigation (beginning with Fielder in the 1970s) of the relationship between the topological structure of a graph and the spectral properties of the corresponding Laplacian matrix. This minisymposium will pursue that theme by exploring, in theoretical and applied settings, connections between the algebraic properties of Laplacian matrices and the nature of the underlying networks.

11:00–11:25 Potential theory for perturbed Laplacian of finite networks
Margarida Mitjana, Universitat Politécnica de Catalunya; E. Bendito, A. Carmona and A.M. Encinas, Universitat Politécnica de Catalunya

11:25–11:50 Subclasses of graphs with partial ordering with respect to the spectral radius of generalized graph Laplacians.
Josef Leydold, WU Vienna University of Economics and Business; Türker Bıyıkoglu, Isık University

11:50–12:15 Some new results on the signless Laplacian of graphs
Slobodan K. Simic, Mathematical Institute of Serbian Academy of Science and Arts

12:15–12:40 Graph bisection from the principal normalized Laplacian eigenvector
Dragan Stevanovic, University of Primorska, UP IAM and University of Nis. PMF

Friday, June 22

MS 72. Linear techniques for solving nonlinear equations
Organizer: Vicente F. Candela Pomares and Rosa M. Peris Sancho
University of Valencia, Spain

A great deal of nonlinear problems are solved by means of linearization processes, where most of the difficulties of nonlinearity are smoothed but inherited by the linear models. Thus, from deconvolution (in image processing), to optimization or ill-posed equations, linear models are developed in order to simplify the problems without losing quality. In this minisymposium we present some of the recent techniques devised to get best performance of linear schemes applied to nonlinear fractional deconvolution, nonlinear variational problems, ill-posedness or nonlinear equations in general, relating both linear and nonlinear worlds.

11:00–11:25 A Gauss-Seidel process in iterative methods for solving nonlinear equations
José Gutiérrez, Universidad de la Rioja; A. Magreñán, University of La Rioja; J. L. Varona, University of La Rioja

11:25–11:50 A greedy algorithm for convergence of a fractional blind deconvolution
Vicente F. Candela, Universidad de Valencia; Pantaleón David Romero Sánchez, Universidad CEU-Cardenal Herrera

11:50–12:15 Overview of iterative methods using a variational approch
Sonia Busquier Sáez, Universidad Politécnica de Cartagena; S. Amat, U.P. Cartagena; P. Pedregal, Universidad de Castilla La Mancha

12:15–12:40 Iterative methods for ill-conditioned problems
Rosa M. Peris Sancho, University of Valencia; Vicente F. Candela, University of Valencia

Friday, June 22

MS 73. Algebraic Riccati equations associated with M-matrices: numerical solution and applications
Organizer: Beatrice Meini
University of Pisa, Italy

Algebraic Riccati equations are a class of matrix equations which model different real world problems. The interest in Riccati equations associated with M-matrices is recent, and is motivated by the relevant applications in fluid queues, stochastic processes and transport theory. The aim of this minisymposium is to bring together people working in applications and people working in numerical linear algebra. In fact, researchers interested in applications are a source of challenging problems; people with expertise in numerical linear algebra can provide highly efficient solution methods. The minisymposium should bring synergetic benefits both to the theoretical and the applied scientific community.

11:00–11:25 Monotone convergence of Newton-like methods for M-matrix algebraic Riccati equations
Chun-Hua Guo, University of Regina, Canada

11:25–11:50 Accurate solution of M-matrix algebraic Riccati equation by ADDA: alternating-directional doubling algorithm
Ren-Cang Li, University of Texas at Arlington, USA

11:50–12:15 When fluid becomes Brownian: the morphing of Riccati into quadratic equations
Giang Nguyen, Université Libre de Bruxelles, Belgium

12:15–12:40 Analyzing multi-type queues with general customer impatience using Riccati equations
Benny Van Houdt, University of Antwerp, Antwerpen, Belgium

Friday, June 22

MS 74. Recent advances in the numerical solution of large scale matrix equations
Organizer: Valeria Simoncini
Università di Bologna, Italy
Organizer: Daniel B. Szyld
Temple University, Philadelphia, USA

Linear and quadratic matrix equations arise in many areas in science and engineering. Very often these equations stem from the discretization of problems involving, possibly three-dimensional, partial differential equations, and thus the matrices have very large dimensions. Therefore, the determination of low rank approximations to the sought-after matrix solution is mandatory. In this minisymposium we present new advances on numerical techniques that specifically address the solution to popular linear and quadratic equations, such as Lyapunov-type and Riccati-type algebraic equations.

11:00–11:25 Hierarchical and Multigrid methods for matrix and tensor equations
Lars Grasedyck, Inst. for Geometry and Practical Mathematics, RWTH Aachen

11:25–11:50 A Survey on Newton-ADI based solvers for large scale AREs
Jens Saak, Max Planck Institute for Dynamics of Complex Technical Systems and Chemnitz University of Technology, DE

11:50–12:15 An invariant subspace method for large-scale algebraic Riccati and Bernoulli equations
Luca Amodei, Université Paul Sabatier, France; Jean-Marie Buchot, Université Paul Sabatier, France

12:15–12:40 Delay Lyapunov equations and model order reduction of time delay systems
Tobias Damm, University of Bayreuth; Elias Jarlebring KTH, Stockholm; Wim Michiels K.U. Leuven, BE

Friday, June 22

MS 75. Points that minimize potential functions
Organizer: Martin Ehler
Helmholtz Zentrum Muenchen, Germany
Organizer: Johann S. Brauchart, Postdoctoral Fellow
The University of New South Wales, Australia

Point distributions that minimize or maximize specific potential functions are used in numerical integration, coding theory, image dithering, and statistical design. Our goal is to investigate optimal configurations on the unit sphere and other manifolds for a range of such functions, including determinants as well as frame-and Riesz-potentials. Minimizers of the frame-potential are analytically characterized by approximation properties of linearly dependent sets. Extrema of determinants and Riesz-potentials on special manifolds are found numerically, and similar approaches yield quasi-uniform samplings on compact manifolds. We aim to identify common themes between research fields, which use extremal configurations, to facilitate synergistic effects.

11:00–11:25 Discretizing compact manifolds with minimal energy
Johann S. Brauchart, The University of New South Wales

11:25–11:50 Well conditioned spherical designs and potential functions
Robert S. Womersley, The University of New South Wales

11:50–12:15 Probabilistic frames in the 2-Wasserstein metric
Kasso Okoudjou, The University of Maryland

12:15–12:40 Numerical minimization of potential energies on specific manifolds
Manuel Gräf, The Chemnitz University of Technology