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Isaac Newton Institute for Mathematical Sciences

Neural Networks and Machine Learning

July - December 1997

Organisers: C M Bishop (Aston), D Haussler (UCSC), G E Hinton (Toronto), M Niranjan (Cambridge), L G Valiant (Harvard)

A Newton Institute EC Summer School


1 - 5 September 1997

Organisers: C M Bishop (Aston) and J Whittaker (Lancaster)

Probabilistic graphical models provide a very general framework for representing complex probability distributions over sets of variables. A powerful feature of the graphical model viewpoint is that it unifies many of the common techniques used in pattern recognition and machine learning including neural networks, latent variable models, probabilistic expert systems, Boltzmann machines and Bayesian belief networks. Indeed, the increasing interactions between the neural computing and graphical modelling communities have resulted in a number of powerful new ideas and techniques. The conference will include several tutorial presentations on key topics as well as advanced research talks.

A provisional programme, including abstracts, is available here.

Provisional themes:

Conditional independence; Bayesian belief networks; message propagation; latent variable models; variational techniques; mean field theory; learning and estimation; model search; EM and MCMC algorithms; axiomatic approaches; causality; decision theory; neural networks; information and coding theory; scientific applications and examples.

Provisional list of speakers:

C M Bishop (Aston) D J C MacKay (Cambridge)
R Cowell (City) J Pearl (UCLA)
A P Dawid (UCL) M D Perlman (Washington)
D Geiger (Technion) M Piccioni (Aquila)
E George (Texas) TS Richardson (Washington)
W Gilks (Cambridge) R Shachter (Stanford)
D Heckerman (Microsoft) J Q Smith (Warwick)
G E Hinton (Toronto) M Studeny (Prague)
T Jaakkola (UCSC) M Titterington (Glasgow)
M I Jordan (MIT) S Russell (Berkeley)
B Kappen (Nijmegen) D Spiegelhalter (Cambridge)
M Kearns (AT&T) J Whittaker (Lancaster)
S Lauritzen (Aalborg)

This instructional conference will form a component of the Newton Institute programme on Neural Networks and Machine Learning, organised by CM Bishop, D Haussler, GE Hinton, M Niranjan and LG Valiant.

Location and Costs: The conference will take place in the Isaac Newton Institute and accommodation for participants will be provided at Wolfson Court, adjacent to the Institute. The conference package costs £270 which includes accommodation from Sunday 31 October to Friday 5 September, together with breakfast, lunch during the days that the lectures take place and evening meals.

Applications: To participate in the conference, please complete and return a grant application form or a registration form for self-supporting applicants. For students and postdoctoral fellows, please also arrange for a letter of reference from a senior scientist. Limited financial support is available for participants from appropriate countries.

Completed forms and letters of recommendation should be sent to Heather Dawson at the Newton Institute.

Closing Date for the receipt of applications and letters of recommendation is 16 June 1997

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