CFP: Learning with Nonparametric Bayesian Methods - ICML 2006 Workshop

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CALL FOR PAPERS / ABSTRACTS

ICML 2006 Workshop

Learning with Nonparametric Bayesian Methods

Pittsburgh, Pennsylvania, June 29, 2006

Deadline for submissions: April 28, 2006

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INTRODUCTION

Dirichlet Processes and other nonparametric Bayesian (NPB) methods
have originally been developed in statistics but are finding
growing interest in the machine learning community. Although the
name indicates otherwise, NPB is concerned with models with an
infinite number of parameters. For machine learning practitioners
this leads to attractive models with (countably) infinite
dimensions in a hidden state space like infinite mixture models.
NPB models have the favorable property that their complexity
automatically adapts to the number of data points. It has already
been demonstrated that in some important machine learning
applications, NPB has clear advantages over parametric solutions.
We hope that this workshop will serve as a platform to discuss
basic issues and recent developments in NPB.


TOPICS AND QUESTIONS WE WANT TO ADDRESS

* General principles:
+ We plan an introductory talk on nonparametric Bayesian methods.

* Current developments:
+ What are the recent developments in the field of NPB?
+ Are there interesting new applications?

* Open problems/new challenges:
+ What are the problem settings for which satisfactory NPB
solutions are still missing due to modeling or inferential
issues?
+ In which areas NPB methods could not demonstrate superior
performance, if compared to parametric solutions?
+ Are there any new challenges arising from recent developments
like spatial, time-varying or transformed Dirichlet processes?

* Computational issues:
+ How can we improve the speed of parameter estimation and
inference?
+ What is the right estimation/inference method for what
setting (MCMC, variational Bayes, empirical Bayes, expectation
propagation)?
+ Are we ready for large data sets, high dimensional data, or
online data processing?


PAPER/ABSTRACT SUBMISSION

We strongly encourage researchers in the area of machine learning,
statistics, natural language processing, computational biology,
information retrieval, and related fields to either submit an
extended abstract (less than 2000 words) or a full paper (4-8
pages). Each submission will be reviewed by at least two reviewers.

Please submit your abstract or paper electronically (PDF or
postscript format) to bickel@xxxxxxxxxxxxxxxxxxxxxxxx It is
recommended to submit papers using the ICML 2006 conference paper
style. Submissions should include the names and contact information
of the authors.


WORKSHOP FORMAT

This will be a one-day workshop immediately after the main ICML
conference. The workshop will interleave invited talks and technical
presentations of the accepted submissions with extensive time for
discussion of the presented work.


IMPORTANT DATES

April 28, 2006: Abstract and paper submission deadline
May 19, 2006: Notification of acceptance
June 09, 2006: Camera ready copy deadline for online workshop
proceedings
June 29, 2006: Workshop


ORGANIZING COMMITTEE

Steffen Bickel
Humboldt University, Berlin, Germany

Volker Tresp
Siemens AG, Corporate Technology, Munich, Germany


PROGRAM COMMITTEE

- Michael Jordan, University of California, Berkeley
- Zoubin Ghahramani, University of Cambridge
- Michael Escobar, University of Toronto
- David Blei, Princeton University
- Yee Whye Teh, National University of Singapore
- Matthew Beal, State University New York, Buffalo
- Thomas Griffiths, Brown University
- David Draper, University of California, Santa Cruz
- Athanasios Kottas, University of California, Santa Cruz
- Larry Wasserman, Carnegie Mellon University
- Kai Yu, Siemens AG, Corporate Technology
- Wray Buntine, Helsinki Institute of Information Technology
- Eric Xing, Carnegie Mellon University
- Jerry Zhu, University of Wisconsin-Madison


For more information, please visit
http://www.informatik.hu-berlin.de/~bickel/npb_workshop.html

We are looking forward to an interesting workshop and encourage
your participation.

Volker Tresp and Steffen Bickel

.

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