CFP: the 2rd International Workshop on Transfer Miming (TM'10) (*Deadline Extension*)
Sinno Jialin Pan
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Please disseminate this CFP in any lists you subscribed and among your
colleagues/students. We also take this chance to invite you to
contribute papers to this workshop. Thanks in advance.
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TM'10: Call For Papers (*The Submission Deadline has been Extended to Aug 9*)
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The 2rd International Workshop on Transfer Mining (TM)
In conjunction wiht IEEE ICDM-2010
Dec 14, 2010, Sydney, Australia.
http://www.cse.ust.hk/~sinnopan/icdm10tm/index.html
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Overview
Traditional data mining algorithms work well under a strict
assumption: the training data and test data are drawn from the same
distribution in the same feature space with the same set of class
labels. In many real world problems, however, we usually do not have
sufficient training data that satisfies this assumption. In order to
apply traditional data mining algorithms, we may need to label a lot
of training data, which is dreadfully expensive. It would be extremely
useful if we can transfer the knowledge from other available data to
our intended task while avoiding the effort of data labeling. In this
workshop, we call for papers on the topic of transfer mining: transfer
learning in data mining. There are several challenges to successfully
transfer knowledge between different tasks. A first challenge is to
judge the relatedness between tasks and avoid negative transfer. A
second challenge is when given related tasks, decide what to transfer.
Tasks may share some hyper-parameters, some features or some
instances. It is nontrivial to decide what kind of knowledge should be
transferred. Finally, how to transfer knowledge efficiently and
effectively is another important issue. Transfer mining, which aims at
transferring of knowledge between different domains and tasks in data
mining, has emerged as one of the most active areas in data mining.
There is a strong need to boost the research on knowledge transfer in
the data mining community. Unlike in ICML/NIPS venues, the workshop
will invite papers that address knowledge transfer from a data mining
perspective. We welcome theoretical and applied disseminations that
make efforts
(1) to expose novel knowledge transfer methodology, frameworks and KDD
processes for transfer mining.
(2) to investigate effective (automated, human-machined-cooperated)
principles and techniques for acquiring, representing, modeling and
engaging transfer mining in real-world data mining.
(3) to project trends and directions of transfer mining in both
theories and applications.
With the success on the 1st International Workshop on Transfer Mining,
the 2nd International Workshop on Transfer Mining will bring active
researchers and industry practitioners together toward developing
next-generation KDD theories. It will also further benefit the
deployment of knowledge discovery in real world applications, and
reduce the gap between data mining and machine learning, industry and
practice.
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Important Dates
- Submission Deadline: Aug 9, 2010.
- Acceptance Notification: September 20, 2010.
- Camera-ready Submission: October 11, 2010.
- Workshop Date: December 14, 2010.
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Submission Introduction:
Paper submissions should be limited to a *maximum* of 8 pages in the
IEEE 2-column format, please go to the following url to see the format
and submission guidelines:
http://datamining.it.uts.edu.au/icdm10/index.php/paper-submissions/submission-guidelines
For submitting papers, please use the submission system via the following url:
http://wi-lab.com/cyberchair/icdm10/scripts/submit.php?subarea=S3&undisplay_detail=1&wh=/cyberchair/icdm10/scripts/ws_submit.php
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Workshop Co-chairs
- Qiang Yang, Hong Kong University of Science and Technology, Hong Kong
- Philip S. Yu, University of Illinois at Chicago, USA
- Gui-Rong Xue, Shanghai Jiaotong University, China
- Sinno Jialin Pan, Hong Kong University of Science and Technology, Hong Kong
- Jing Jiang, Singapore Management University, Singapore
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