OEDM 2010 - 2010 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'10)

This workshop (OEDM’10) is a continuation of the theme of ICDM 2009 workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM’09). OEDM’09 is the first workshop on optimization-based methods for emerging data mining problems held annually with the ICDM Conference. The workshop builds on the success of previous workshop and provides a unique platform for researchers and practitioners working on data mining using optimization based techniques to share and disseminate recent research results.

Classical optimization techniques have found widespread use in solving various data mining problems, among which convex optimization has occupied the center-stage because of its elegant property of global optimum. Many problems can be cast into the convex optimization framework, such as Support Vector Machines, graph-based manifold learning, and clustering, which can usually be solved by convex Quadratic Programming, Semi-Definite Programming or Eigenvalue Decomposition.

As time goes by, new problems emerge constantly in data mining community, such as Time-Evolving Data Mining, On-Line Data Mining, Relational Data Mining and Transferred Data Mining. Some of these recently emerged problems are more complex than traditional ones and are usually formulated as nonconvex problems. Therefore some general optimization methods, such as gradient descents, coordinate descents, convex relaxation, have come back to the stage and become more and more popular in recent years.

This workshop will present recent advances in optimization techniques for, especially new emerging, data mining problems, as well as the real-life applications among. One main goal of the workshop is to bring together the leading researchers who work on state-of-the-art algorithms on optimization based methods for modern data analysis, and also the practitioners who seek for novel applications. In summary, this workshop will strive to emphasize the following aspects:

Presenting recent advances in algorithms and methods using optimization techniques
Addressing the fundamental challenges in data mining using optimization techniques
Identifying killer applications and key industry drivers (where theories and applications meet)
Fostering interactions among researchers (from different backgrounds) sharing the same interest to promote cross-fertilization of ideas.
Exploring benchmark data for better evaluation of the techniques