NATO-ASI on Learning Theory and Practice - Leuven 2002

General Objective

This NATO Advanced Study Institute on Learning Theory and Practice aims at creating a fascinating interplay between advanced fundamental theory and several application areas such as bioinformatics, multimedia/computer vision, e-commerce/finance, internet search, textmining and others. It offers an interdisciplinary forum for presenting recent progress and breakthroughs in learning theory with respect to several areas as neural networks, machine learning, mathematics and statistics.

Invited Lecturers

• Peter Bartlett (Australian National University Canberra, AUS)
  ``Computational learning theory and reinforcement learning'' [ ps.gz ]
  
  
• Sankar Basu (NSF Arlington, USA)
  ``Parametric density estimation and speech recognition''
  
  
• Kristin Bennett (Rensselaer Polytechnic Institute New York, USA)
  `` Mathematical programming approaches to SVMs with applications to intelligent design of materials and virtual design of pharmaceuticals'' [ ppt ]
  
  
• Chris Bishop (Microsoft Research Cambridge, UK)
  ``Probabilistic graphical models and their role in machine learning'' [ 1|pdf | 2|pdf ]
  
  
• Nello Cristianini (Royal Holloway London, UK)
  ``Support vector and kernel machines with bioinformatics and textmining applications'' [ 1|pdf | 2|pdf ]
  
  
• Luc Devroye (McGill University Montreal, CAN)
  ``Non-parametric learning''
  
  
• Lazlo Gyorfi (T.U. Budapest, HUN)
  ``Non-parametric prediction'' [ ps ]
  
  
• Gabor Horvath (T.U. Budapest, HUN)
  ``Neural networks for measurement systems'' [ pdf ]
  
  
• Rudolf Kulhavy (Honeywell Prague Laboratory, CZ)
  ``Bayesian smoothing and information geometry'' [ pdf ]
  
  
• Vera Kurkova (Academy of Sciences of the Czech Republic, CZ)
  ``Approximation by feedforward neural networks''
  
  
• Joerg Lemm (University of Muenster, GER)
  ``Bayesian field theory with applications to density estimation, classification, regression, and inverse quantum theory'' [ ps.gz ]
  
  
• Charles Micchelli (State University of New York, USA)
  ``Parametric density estimation and speech recognition''
  
  
• Tomaso Poggio (MIT, USA)
  ``Learning machines and applications'' [ pdf ]
  
  
• Massimiliano Pontil (University of Siena, IT)
  ``Ensembles of kernel machines'' [ pdf ]
  
  
• Bernhard Schoelkopf (Max-Planck-Institute Tuebingen, GER)
  ``Learning with kernels'' [ ps.gz | canu.pdf ]
  
  
• Yoram Singer (Hebrew University Jerusalem, IS)
  ``Machine learning for information retrieval'' [ 1|pdf | 2|pdf ]
  
  
• Steve Smale (U.C. Berkeley, USA)
  ``Mathematical foundations of learning theory'' [ pdf ]
  
  
• Johan Suykens (K.U. Leuven, BEL)
  ``Least squares support vector machines'' [ 1|pdf | 2|html ]
  
  
• Vladimir Vapnik (NEC Research Institute, USA)
  ``Statistical learning theory'' [ pdf ]
  
  
• Mathukumalli Vidyasagar (Tata Consultancy Services, IND)
  ``Applications of statistical learning theory to bioinformatics'' [ 1|ps | 2|ps ]