SDM13: Call for Tutorials
Crowdsourcing & Human Computation for Data Labeling & Building Hybrid Systems - slides
Matthew Lease, University of Texas at Austin, USA
Outlier Detection for Temporal Data - PDF [8.5MB]
Manish Gupta, University of Illinois at Urbana-Champaign, USA
Jing Gao, State University of New York, Buffalo, USA
Charu Aggarwal, IBM T. J. Watson Research Center, USA
Jiawei Han, University of Illinois at Urbana-Champaign, USA
Online Learning for Big Data Mining: Methods and Applications - PDF [5MB]
Steven C.H. Hoi, Nanyang Technological University, Singapore
Sampling and Summarization for Social Networks - PDF [2MB]
Shou-De Lin, National Taiwan University, Taiwan
Mi-Yen Yeh, Institute of Information Science, Academia Sinica, Taiwan
Cheng-Te Li, National Taiwan University, Taiwan
The SIAM Data Mining (SDM13) 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 SDM13, 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 and SDM12.
Tutorials are open to all conference attendees without any extra fees. The typical tutorial will be 2 hrs long (longer tutorials will be considered). Previous SDM conferences attracted up to 100 attendees in a tutorial.
Proposals should be submitted electronically by September 30, 2012 11:59 PM PST to:
Computer Science and Engineering
Arizona State University
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).
- Special equipment (if any): Please indicate any additional equipment needed (if any). The standard equipment includes an LCD projector and single projection screen.
- Submission : September 30, 2012 11:59 PM PST
- Decision Notification : October 31, 2012
- Complete Set of Tutorial Viewgraphs (Slides): February 14, 2013