Learning Theoretic and Bayesian Inductive Principles

EU PASCAL Workshop on

Learning Theoretic and Bayesian Inductive Principles

19-21 July 2004

Gatsby Computational Neuroscience Unit

University College London, UK

The theoretical analysis of systems that learn from data has been an important topic of study in statistics, machine learning, and information theory. Formal tools for this analysis have been developed from distinct inductive paradigms, such as Bayesian inference, statistical learning theory, and minimum description length. In recent years, there has been a convergence of ideas from these distinct paradigms, an example of which are PAC-Bayesian bounds on generalisation performance. The goal of this workshop is to bring together leading theoreticians to allow them to debate, compare and cross-fertilise ideas from these distinct inductive principles.

The format of the workshop will be 90 minute talks from invited speakers, short talks from contributed speakers, and ample discussion time.

We invite original contributions to the workshop that will undergo a short refereeing process. Please describe the work in 1-4 pages specifying the model that you adopt and outlining the results/contribution. We encourage blue-skies ideas but they should be sufficiently concrete to be clear and understandable. The deadline for contributions is 31 May 2004.

SCHEDULE OF PRESENTATIONS

IMPORTANT DATES:

Deadline for Contributions:31 May 2004 Instructions for Submission
Notification of Acceptance:14 Jun 2004
Registration Deadline: 28 Jun 2004 Registration is limited to 45 participants; see Registration Instructions
Workshop Dates: 19-21 Jul 2004

INVITED SPEAKERS:

Peter Bartlett, University of California at Berkeley, USA
Olivier Catoni, Universite Paris 6, France
A Philip Dawid, University College London, UK
Claudio Gentile, Universita dell'Insubria, Italy
Gabor Lugosi, Pompeu Fabra University, Spain
John Langford, Toyota Technological Institute, USA
David MacKay, University of Cambridge, UK
Paul Vitanyi, CWI, Netherlands

ORGANISERS:

Zoubin Ghahramani, University College London, UK
John Shawe-Taylor, University of Southampton, UK

PROGRAMME COMMITTEE:

Zoubin Ghahramani, University College London, UK
Peter Grünwald, CWI, Netherlands
John Langford, Toyota Technological Institute, USA
Gabor Lugosi, Pompeu Fabra University, Spain
Shahar Mendelson, Australian National University, Australia
John Shawe-Taylor, University of Southampton, UK

PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning, http:///www.pascal-network.org) is a newly launched (December 2003) European Network of Excellence (NoE) as part of its IST program. The NoE brings together experts from basic research areas such as Statistics, Optimisation and Computational Learning and from a number of application areas, with the objective of integrating research agendas and improving the state of the art in all concerned fields with emphasis on applications in multi-modal interfaces.

Zoubin Ghahramani
Last modified: Sun Jun 27 02:54:30 BST 2004