SDM18: Call for Tutorials
A Critical Review of Online Social Data: Biases, Methodological: Pitfalls, and Ethical Boundaries
Authors: Alexandra Olteanu (IBM Research), Emre Kıcıman (Microsoft Research), Carlos Castillo (Universitat Pompeu Fabra)
Data Mining Critical Infrastructure Systems - Models and Tools
Authors: Liangzhe Chen (Virginia Tech), B. Aditya Prakash (Virginia Tech)
Knowledge Discovery from Temporal Social Networks
Authors: Fabíola S. F. Pereira (Federal University of Uberlandia, Brazil), João Gama (University of Porto, Portugal)
Problems with Partially Observed (Incomplete) Networks: Biases, Skewed Results, and Solutions
Authors: Tina Eliassi-Rad (Northeastern University), Sucheta Soundarajan (Syracuse University), Sahely Bhadra (IIT Palakkad)
The Canonical Polyadic Tensor: Decomposition and Variants for Mining Multi-Dimensional Data
Authors: Tamara G. Kolda and Jed A. Duersch, Sandia National Laboratories
The SIAM Data Mining (SDM18) Organizing Committee invites proposals for tutorials to be held in conjunction with the conference. Tutorials are an effective way to educate and/or provide the necessary background to the intended audience enabling them to understand technical advances.
For SDM18, we are seeking proposals for tutorials on all topics related to data mining. A tutorial may be a theme-oriented comprehensive survey, discuss novel data mining techniques or may center around successful and timely application of data mining in important application areas (e.g., medicine, national security, scientific data analysis). Tutorials on interdisciplinary research topics, novel and fast growing directions, and innovative applications are highly encouraged. For examples of typical SIAM tutorials, see the set of accepted tutorials at previous SIAM conferences SDM14, SDM15, SDM16 and SDM17.
Tutorials are open to all conference attendees without any extra fees. The typical tutorial will be 2 hours long (longer tutorials will be considered). Previous SDM conferences attracted up to 100 attendees in a tutorial.
Proposals should be submitted electronically with subject heading: “SDM 2018 Tutorial Proposal Submission” by October 6, 2017 11:59PM (US Pacific Time) to:
University of Southern California, USA
Proposals should be submitted in PDF format (for other formats please contact the tutorial chair first).
Proposals should include the following:
- Basic information: Title, brief description, name and contact information for each tutor, length of the proposed tutorial. If the intended tutorial is expected to take longer than 2 hours a rationale is expected. Also identify any other venues in which the tutorial has been or will be presented.
- Audience: Proposals must clearly identify the intended audience for the tutorial (e.g., novice, intermediate, expert).
- What background will be required of the audience?
- Why is this topic important/interesting to the SIAM data mining community?
- What is the benefit to participants?
- Provide some informal evidence that people would attend (e.g., related workshops).
- Coverage: Enough material should be included to provide a sense of both the scope of material to be covered and the depth to which it will be covered. The more details that can be provided, the better (up to and including links to the actual slides or viewgraphs). Note that the tutors should not focus mainly on their own research results. If, for certain parts of the tutorial, the material comes directly from the tutors' own research or product, please indicate this clearly in the proposal.
- Biographies: Provide brief biographical information on each tutor (including qualifications with respect to the tutorial's topic).
- Submission : October 6, 2017 11:59PM (US Pacific Time)
- Decision Notification : November 6, 2017
- Complete Set of Tutorial Viewgraphs (Slides): February 14, 2018