Connectionists: FINAL Call for contributions: NIPS 2009 Workshop on Understanding Multiple Kernel Learning Methods

[Gert Lanckriet]

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FINAL Call for contributions - Understanding Multiple Kernel Learning  
Methods

Submission deadline: November 3rd, 2009.

http://mkl.ucsd.edu/workshop

Workshop at the Twenty-Third Annual Conference on Neural Information  
Processing Systems (NIPS 2009), Whistler, BC, Canada, December 11 or  
12, 2009.
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DESCRIPTION

Multiple kernel learning has been the subject of nearly a decade of  
research. Designing and integrating kernels has proven to be an  
appealing approach to address several, challenging real world  
applications, involving multiple, heterogeneous data sources in  
computer vision, bioinformatics, audio processing problems, etc. The  
goal of this workshop is to step back and evaluate the achievements of  
multiple kernel learning in the past decade, covering a variety of  
applications.

In short, this workshop seeks to understand where and how kernel  
learning is relevant (with respect to accuracy, interpretability,  
feature selection, etc.), rather than exploring the latest  
optimization techniques and extension formulations.  More  
specifically, the workshop envisions to discuss the following two  
questions:

-- 1 -- Kernel learning vs. kernel design: Does kernel learning offer  
a practical advantage over the manual design of kernels?

-- 2 -- Given a set of kernels, what is the optimal way, if any, to  
combine them (sums, products, learned or non learned, with or without  
cross-validation)?

We are seeking participants interested in presenting their work and  
relating their experience in the workshop, providing insight on the  
above two questions. This includes evidence of MKL improving accuracy  
beyond any existing method based on single kernels (provided with  
insights as to why there is such improvement), as well as evidence of  
the opposite (with insights as to why). We welcome presentation of  
recent results, as well as presentations based on previously published  
work that shed light on the above questions.

If you are interested in participating and contributing a  
presentation, please send an email to bmcfee at cs.ucsd.edu with an  
abstract or a summary, by Tuesday November 3rd, 2009. If the  
presentation is based on previously published work, please include  
details of such publications.


REPOSITORY

In conjunction with the workshop, we are establishing an open  
repository of data sets for use with MKL algorithms.  Authors are  
encouraged to contribute data to the MKL Repository (mkl.ucsd.edu),  
and use the repository to benchmark new algorithms.


ORGANIZERS

    * Gert Lanckriet (University of California, San Diego), gert at ece.ucsd.edu
    * Francis Bach (Ecole Normale Superieure/INRIA), francis.bach at ens.fr
    * Nathan Srebro (Toyota Technological Institute, Chicago), nati at uchicago.edu
    * Brian McFee (University of California, San Diego), bmcfee at cs.ucsd.edu
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