ICANN 1999
Gaussian Process Classifiers and Support Vector Machines
Organizers: Carl Rasmussen, Roderick Murray-Smith, Alex Smola, Chris Williams
Location: University of Edinburgh, September 11, 1999
Abstract
This workshop aims to bring together people working with Gaussian Process (GP) and Support Vector Machine (SVM) predictors for regression and classification problems. We will open with tutorial-like introductions to the basics so that researchers new to the area can gain an impression of the applicability of the approaches, and will follow with contributed presentations. The final part of the workshop will be an open discussion session. We would bring laptops to provide some software demos, and would encourage others to do the same.
Topics
- Methods for choosing kernels:
- Generic vs problem specific issues
- Uniform convergence and Bayesian theory
- Efficient implementation/approximation of GP and SVM predictors on large datasets
- GP classifiers: MCMC methods, variational and Laplace approximations
- Kernel methods for dynamic system modelling
- Applications of Kernel methods
- Reproducing Kernel Hilbert Spaces
Date and Location
The workshop was held on Saturday 11 September 1999 as part of the ICANN 99 workshops, in the Appleton Tower at the University of Edinburgh.