Call for Contributions: NIPS 2009 Workshop on Nonparametric Bayes
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Dilan Gorur
Sep 14, 2009, 12:24:05 PM9/14/09
to Machine Learning News, npbay...@googlemail.com
Apologies for cross-posting. Please forward this to those who may be
interested. Thank you.
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Call for Abstracts and Participation
NIPS 2009 WORKSHOP on NONPARAMETRIC BAYES 2009
December 11/12, 2009
http://npbayes-2009.wikidot.com
abstract submission deadline: Wednesday, October 21st
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
BACKGROUND
One of the major problems driving current research in statistical
machine learning is the search for ways to exploit highly-structured
models that are both expressive and tractable. Bayesian nonparametrics
provides a framework for developing robust and flexible models that
can accurately represent the complex structure in the data. Model
flexibility is achieved by assigning priors with unbounded capacity
and overfitting is prevented by integrating out all parameters and
latent variables.
Current work has established results on asymptotic behaviour of simple
Bayesian nonparametric models. Most of the results are for simple
cases, such as density estimation and Gaussian process regression.
However, there is a steady development of tools, which are starting to
allow us to tackle much more challenging models. We have invited
experts to comment and provide guidance on discussion on this topic.
We also invite theoreticians within the NIPS community to participate
in this focus.
It is essential to provide easy to follow guidance for the model
structure specification and the choice of hyperparameters. A step
towards this direction is the discussion of an objective or empirical
Bayes treatment. Additionally, developing general purpose software
that can scale up inference techniques to massive datasets would is
another step necessary for the wide applicability of these models.
This workshop will help us summarize the current state of the
practical use of nonparametric Bayesian models and focus on the
requirements of the field to extend its use in other application
domains.
WORKSHOP
We aim to bring together researchers to create a forum for discussing
recent advances in Bayesian nonparametrics, to understand better the
asymptotic properties of the models and to inspire research on new
techniques for better models and inference algorithms.
The workshop will focus mainly on two important issues. 1) Theoretical
properties of complex Bayesian nonparametric models, in particular
asymptotics (e.g. consistency, rates of convergence, and Bernstein von-
Mises results). 2) Practical matters to enable the use of Bayesian
nonparametrics in real world applications such as developing general
purpose software, discussion of an objective or empirical Bayes
treatment. Each focus will be given a specific session during the
workshop.
This is the fifth in a series of successful workshops on this topic.
The first two were at NIPS 2003 and 2005 and the last two were at ICML
2006 and 2008. The field attracts researchers from a broad range of
disciplines, ranging from theoretical statisticians and probabilists
to people working on specialized applications. This workshop aims to
enhance the interaction between these communities which has been
initiated by previous workshops in order to exchange ideas, discuss
future directions, and build collaborative efforts.
The workshop will consist of 5 invited talks, 4 contributed talks, a
session for informal impromptu talks and a poster session.
INVITED SPEAKERS (confirmed)
Zoubin Ghahramani, University of Cambridge
http://learning.eng.cam.ac.uk/zoubin/
Subhashis Ghoshal, North Carolina State University
http://www4.stat.ncsu.edu/~sghosal/
Alejandro Jara, Universidad de Concepción
http://www2.udec.cl/~ajarav/
CALL FOR PARTICIPATION
Researchers interested in presenting their work and ideas on Bayesian
nonparametrics at the workshop should send an email to
npbay...@googlemail.com with the following information:
Title
Authors
Abstract (maximum 3 pages, NIPS style pdf)
Preferred contribution (talk, poster, and/or round-table
participation)
We expect authors to provide a final version of their papers by early
December for inclusion on the workshop home page. Papers chosen for
contributed talks shall also be expected to liaise with a discussion
leader who will be in charge of stimulating discussion of the work at
the workshop.
DATES
Abstracts due: Oct 21, 2009
Notifications: Nov 4, 2009
Final paper due: Dec 2, 2009
Workshop: Dec 11/12, 2009
LOCATION
Westin Resort and Spa / Hilton Whistler Resort and Spa
Whistler, B.C., Canada
https://nips.cc/Conferences/2009/
ORGANIZERS
Dilan Gorur, Gatsby Computational Neuroscience Unit
François Caron, INRIA Bordeaux Sud-Ouest
Yee Whye Teh, Gatsby Computational Neuroscience Unit
David Dunson, Duke University
Zoubin Ghahramani, University of Cambridge
Michael I. Jordan, University of California at Berkeley
CONTACT
npbay...@googlemail.com
Your expertise, experience and perspective are very valuable to making
the workshop a success. Thank you very much, and we hope to see you at
the workshop!
Dilan Gorur, François Caron, Yee Whye Teh, David Dunson, Zoubin
Ghahramani and Michael I. Jordan.
http://npbayes-2009.wikidot.com/
interested. Thank you.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Call for Abstracts and Participation
NIPS 2009 WORKSHOP on NONPARAMETRIC BAYES 2009
December 11/12, 2009
http://npbayes-2009.wikidot.com
abstract submission deadline: Wednesday, October 21st
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
BACKGROUND
One of the major problems driving current research in statistical
machine learning is the search for ways to exploit highly-structured
models that are both expressive and tractable. Bayesian nonparametrics
provides a framework for developing robust and flexible models that
can accurately represent the complex structure in the data. Model
flexibility is achieved by assigning priors with unbounded capacity
and overfitting is prevented by integrating out all parameters and
latent variables.
Current work has established results on asymptotic behaviour of simple
Bayesian nonparametric models. Most of the results are for simple
cases, such as density estimation and Gaussian process regression.
However, there is a steady development of tools, which are starting to
allow us to tackle much more challenging models. We have invited
experts to comment and provide guidance on discussion on this topic.
We also invite theoreticians within the NIPS community to participate
in this focus.
It is essential to provide easy to follow guidance for the model
structure specification and the choice of hyperparameters. A step
towards this direction is the discussion of an objective or empirical
Bayes treatment. Additionally, developing general purpose software
that can scale up inference techniques to massive datasets would is
another step necessary for the wide applicability of these models.
This workshop will help us summarize the current state of the
practical use of nonparametric Bayesian models and focus on the
requirements of the field to extend its use in other application
domains.
WORKSHOP
We aim to bring together researchers to create a forum for discussing
recent advances in Bayesian nonparametrics, to understand better the
asymptotic properties of the models and to inspire research on new
techniques for better models and inference algorithms.
The workshop will focus mainly on two important issues. 1) Theoretical
properties of complex Bayesian nonparametric models, in particular
asymptotics (e.g. consistency, rates of convergence, and Bernstein von-
Mises results). 2) Practical matters to enable the use of Bayesian
nonparametrics in real world applications such as developing general
purpose software, discussion of an objective or empirical Bayes
treatment. Each focus will be given a specific session during the
workshop.
This is the fifth in a series of successful workshops on this topic.
The first two were at NIPS 2003 and 2005 and the last two were at ICML
2006 and 2008. The field attracts researchers from a broad range of
disciplines, ranging from theoretical statisticians and probabilists
to people working on specialized applications. This workshop aims to
enhance the interaction between these communities which has been
initiated by previous workshops in order to exchange ideas, discuss
future directions, and build collaborative efforts.
The workshop will consist of 5 invited talks, 4 contributed talks, a
session for informal impromptu talks and a poster session.
INVITED SPEAKERS (confirmed)
Zoubin Ghahramani, University of Cambridge
http://learning.eng.cam.ac.uk/zoubin/
Subhashis Ghoshal, North Carolina State University
http://www4.stat.ncsu.edu/~sghosal/
Alejandro Jara, Universidad de Concepción
http://www2.udec.cl/~ajarav/
CALL FOR PARTICIPATION
Researchers interested in presenting their work and ideas on Bayesian
nonparametrics at the workshop should send an email to
npbay...@googlemail.com with the following information:
Title
Authors
Abstract (maximum 3 pages, NIPS style pdf)
Preferred contribution (talk, poster, and/or round-table
participation)
We expect authors to provide a final version of their papers by early
December for inclusion on the workshop home page. Papers chosen for
contributed talks shall also be expected to liaise with a discussion
leader who will be in charge of stimulating discussion of the work at
the workshop.
DATES
Abstracts due: Oct 21, 2009
Notifications: Nov 4, 2009
Final paper due: Dec 2, 2009
Workshop: Dec 11/12, 2009
LOCATION
Westin Resort and Spa / Hilton Whistler Resort and Spa
Whistler, B.C., Canada
https://nips.cc/Conferences/2009/
ORGANIZERS
Dilan Gorur, Gatsby Computational Neuroscience Unit
François Caron, INRIA Bordeaux Sud-Ouest
Yee Whye Teh, Gatsby Computational Neuroscience Unit
David Dunson, Duke University
Zoubin Ghahramani, University of Cambridge
Michael I. Jordan, University of California at Berkeley
CONTACT
npbay...@googlemail.com
Your expertise, experience and perspective are very valuable to making
the workshop a success. Thank you very much, and we hope to see you at
the workshop!
Dilan Gorur, François Caron, Yee Whye Teh, David Dunson, Zoubin
Ghahramani and Michael I. Jordan.
http://npbayes-2009.wikidot.com/
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