SDM16: Call for Tutorials
Accepted Tutorials
Mining Personal Traits in Social Media
Presenters: Aron Culotta, Illinois Institute of Technology, USA and Dongwon Lee, Pennsylvania State University, USA
Optimal Connectivity on Big Graphs: Measures, Algorithms and Applications
Presenter: Hanghang Tong, Arizona State University, USA
Large Scale Hierarchical Classification: Foundations, Algorithms and Applications
Presenters: Huzefa Rangwala, George Mason University, USA and Azad Naik, George Mason University, USA
Biomedical Data Mining with Matrix Models
Presenters: Fei Wang, University of Connecticut, USA and Ping Zhang, IBM Thomas J. Watson Research Center, USA
Problems with Incomplete Networks: Biases, Skewed Results, and Solutions
Presenters: Tina Eliassi-Rad Rutgers University, USA, Sucheta Soundarajan, Syracuse University, USA, Ali Pinar, Sandia National Lab, USA and Brian Gallagher, Lawrence Livermore National Laboratory, USA
Towards Veracity Challenge in Big Data
Presenters: Jing Gao, Qi Li, Bo Zhao, Wei Fan, and Jiawei Han
SUNY Buffalo, Buffalo, NY USA, LinkedIn, Mountain View, CA USA, Baidu Research Big Data Lab, China, University of Illinois, Urbana, IL USA
The SIAM Data Mining (SDM16) 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 SDM16, 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). For examples of typical SIAM tutorials, see the set of accepted tutorials at previous SIAM conferences SDM11, SDM12, SDM13, SDM14, and SDM15.
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 2016 Tutorial Proposal Submission” by October 9, 2015, 11:59 PM (US Pacific Time) to:
Prof. Tao Li
School of Computing and Information Sciences
Florida International University
[email protected]
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).
Timeline
- Submission: October 9, 2015, 11:59 PM (US Pacific Time)
- Decision Notification : November 9, 2015
- Complete Set of Tutorial Viewgraphs (Slides): February 16, 2016
