Conference Information
SDM 2017 : SIAM International Conference on Data Mining
http://www.siam.org/meetings/sdm17/
Submission Date:
2016-10-08
Notification Date:
2016-12-19
Conference Date:
2017-04-27
Location:
Houston, Texas, USA
Years:
17
CCF: b   CORE: a   QUALIS: a2   Viewed: 16545   Tracked: 40   Attend: 3

Conference Location
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Call For Papers
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

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To RSVP to the conference on Facebook and connect with other attendees, find roommates etc., please visit https://www.facebook.com/events/475483799321188/ .

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 #SIAMSDM17. SIAM’s Twitter handle is @TheSIAMNews.
 

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

Conference Co-Chairs
Carlotta Domeniconi, George Mason University, USA
Dimitrios Gunopulos, University of Athens, Greece

Program Co-Chairs
Nitesh Chawla, University of Notre Dame, USA
Wei Wang, University of California, Los Angeles, USA

Workshops Co-Chairs
Leman Akoglu, Stony Brook University, The State University of New York, USA
Arthur Zimek, Ludwig-Maximilians-Universität München, Germany

Tutorials Chair
Jilles Vreeken, Saarland University and Max Planck Institute for Informatics, Germany

Doctoral Forum Chair
Shuiwang Ji, Washington State University, USA

Sponsorship Co-Chairs
James Faghmous, Icahn School of Medicine, Mount Sinai, USA
Jiliang Tang, Yahoo Research, USA

Panels Chair
Chris Jermaine, Rice University, USA

Publicity Co-Chairs
Danai Koutra, University of Michigan, USA
Matthijs van Leeuwen, Leiden University, The Netherlands
Panagiotis Papapetrou, Stockholm University, Sweden

Awards Chair
Zoran Obradovic, Temple University, 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 Agency

nsfSIAM 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

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
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 and Information Network Analyses
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 8, 2016, 11:59 PM (US Pacific Time): Abstract Submission
October 8, 2016, 11:59 PM (US Pacific Time): Workshop Proposals
October 8, 2016, 11:59 PM (US Pacific Time): Tutorial Proposals
October 15, 2016, 11:59 PM (US Pacific Time): Paper Submission

TRAVEL FUND APPLICATION DEADLINE
January 27, 2017: SIAM Student Travel Award and Post-doc/Early Career Travel Award Applications

PRE-REGISTRATION RATE DEADLINE
March 30, 2017: Disconnect time is midnight EDT

HOTEL RESERVATION DEADLINE 
March 28, 2017

Last updated by Dou Sun in 2016-09-11
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