Sponsored by the SIAM Activity Group on Data Mining and Analytics.
This conference is held in cooperation with the American Statistical Association.
Statement on Inclusiveness
As a professional society, SIAM is committed to providing an inclusive climate that encourages the open expression and exchange of ideas, that is free from all forms of discrimination, harassment, and retaliation, and that is welcoming and comfortable to all members and to those who participate in its activities. In pursuit of that commitment, SIAM is dedicated to the philosophy of equality of opportunity and treatment for all participants regardless of gender, gender identity or expression, sexual orientation, race, color, national or ethnic origin, religion or religious belief, age, marital status, disabilities, veteran status, field of expertise, or any other reason not related to scientific merit. This philosophy extends from SIAM conferences, to its publications, and to its governing structures and bodies. We expect all members of SIAM and participants in SIAM activities to work towards this commitment.
Announcements
Local Area Restaurant List [PDF, 80KB]
Doctoral Student Forum
Click here to view the list of participants for the Doctoral Student Forum. [PDF, 70KB]
Applications for participation in the doctoral forum are due March 7, 2016. Click here for the Call for Doctoral Student Forum Participants.
To RSVP to the conference on Facebook and connect with other attendees, find roommates etc., please visit https://www.facebook.com/events/1612527895694215/.
If you are tweeting about the conference, please use the designated hashtag to enable other attendees to keep up with the Twitter conversation and to allow better archiving of our conference discussions. The hashtag for this meeting is #SIAMSDM16.
Organizing Committee
Steering Committee Chair
Srinivasan Parthasarathy, Ohio State University, USA
Steering Committee
Chid Apte, IBM T.J. Watson Research Center, USA
Christos Faloutsos, Carnegie Mellon University, USA
Joydeep Ghosh The University of Texas at Austin, USA
Jiawei Han, University of Illinois at Urbana-Champaign, USA
Chandrika Kamath, Lawrence Livermore National Laboratory, USA
Vipin Kumar, University of Minnesota, USA
Haesun Park, Georgia Institute of Technology, USA
Srinivasan Parthasarathy, Ohio State University, USA
Qiang Yang Hong Kong University of Science and Technology, USA
Philip Yu, University of Illinois at Chicago, USA
Qiang Yang Hong Kong University of Science and Technology, USA
Conference Co-Chairs
Carlotta Domeniconi, George Mason University, USA
Ke Wang, Simon Fraser University, Canada
Program Co-Chairs
Sanjay Chawla, Qatar Computing Research Institute, Qatar and University of Sydney, Australia
Wagner Meira, Universidade Federal de Minas Gerais, Brazil
Workshop Co-Chairs
Tanya Berger-Wolf, University of Illinois, Chicago, USA
David Gleich, Purdue University, USA
Tutorial Chair
Tao Li, Florida International University, USA
Doctoral Forum Chair
Mitsunori Ogihara, University of Miami, USA
Publicity Co-Chairs
B. Aditya Prakash, Virginia Tech, USA
Venu Satuluri, Twitter, USA
Panel Chair
Wei Wang, University of California at Los Angeles, USA
Sponsorship Co-Chairs
Nitesh Chawla, University of Notre Dame, USA
Philip Kegelmeyer, Sandia National Laboratories, USA
Description
Data mining is the computational process for discovering valuable knowledge from data. It has enormous application in numerous fields, including science, engineering, healthcare, business, and medicine. Typical datasets in these fields are large, complex, and often noisy. Extracting knowledge from these datasets requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms, which are based on sound theoretical and statistical foundations. These techniques in turn require implementations on high performance computational infrastructure that are carefully tuned for performance. Powerful visualization technologies along with effective user interfaces are also essential to make data mining tools appealing to researchers, analysts, and application developers from different disciplines.
The SDM conference provides a venue for researchers who are addressing these problems to present their work in a peer-reviewed forum. It also provides an ideal setting for graduate students and others new to the field to learn about cutting-edge research by hearing outstanding invited speakers and attending presentations and tutorials (included with conference registration). A set of focused workshops is also held on the last day of the conference. The proceedings of the conference are published in archival form, and are also made available on the SIAM web site.
Funding Agencies
SIAM and the Conference Organizing Committee wish to extend their thanks and appreciation to the U.S. National Science Foundation for its support of this conference.
Themes and Topics of Interest
Methods and Algorithms
- Classification
- Clustering
- Frequent Pattern Mining
- Probabilistic & Statistical Methods
- Graphical Models
- Spatial & Temporal Mining
- Data Stream Mining
- Anomaly & Outlier Detection
- Feature Extraction, Selection and Dimension Reduction
- Mining with Constraints
- Data Cleaning & Preprocessing
- Computational Learning Theory
- Multi-Task Learning
- Online Algorithms
- Big Data, Scalable & High-Performance Computing Techniques
- Mining with Data Clouds
- Mining Graphs
- Mining Semi Structured Data
- Mining Complex Datasets
- Mining on Emerging Architectures
- Text & Web Mining
- Optimization Methods
- Other Novel Methods
Applications
- Astronomy & Astrophysics
- High Energy Physics
- Collaborative Filtering
- Recommender Systems
- Climate / Ecological / Environmental Science
- Risk Management
- Supply Chain Management
- Customer Relationship Management
- Finance
- Genomics & Bioinformatics
- Drug Discovery
- Healthcare Management
- Automation & Process Control
- Logistics Management
- Intrusion & Fraud detection
- Bio-surveillance
- Sensor Network Applications
- Social Network Analysis
- Educational Data Mining
- Intelligence Analysis
- Other Novel Applications & Case Studies
Human Factors and Social Issues
- Ethics of Data Mining
- Intellectual Ownership
- Privacy Models
- Privacy Preserving Data Mining & Data Publishing
- Risk Analysis
- User Interfaces
- Interestingness & Relevance
- Data & Result Visualization
- Other Human Factors and Social Issues
Important Deadlines
SUBMISSION DEADLINES
October 9, 2015, 11:59 PM (US Pacific Time): Abstract Submission
October 9, 2015, 11:59 PM (US Pacific Time): Workshop Proposals
October 9, 2015, 11:59 PM (US Pacific Time): Tutorial Proposals
October 16, 2015, 11:59 PM (US Pacific Time): Paper Submission
December 21, 2015: Author Notification
January 25, 2016: Camera Ready Papers Due
TRAVEL FUND APPLICATION DEADLINE
January 29, 2016
PRE-REGISTRATION DEADLINE
April 7, 2016: Disconnect time is 4:00 PM EDT
HOTEL INFORMATION
April 7, 2016