Neural Information Processing Systems

Tutorial Program

Mostly statistical methods for language processing, Dan Jurafsky, University of Colorado at Boulder
From traditional statistical models to neural networks, Trevor Hastie, Stanford University

Practical pattern recognition via neural networks, Brian Ripley, University of Oxford
Reinforcement learning, Richard S. Sutton, University of Massachusetts

Neural networks for the human genome project and beyond, Frank Eeckman, Lawrence Berkeley National Laboratory
Challenges of time series prediction, John Moody, Oregon Graduate Institute

We have attempted to ensure that all information is correct, but we cannot guarantee it.

Please send comments and corrections to:

L. Douglas Baker

Carnegie Mellon University