Sciweavers

Share
NIPS
1994
8 years 8 months ago
An Alternative Model for Mixtures of Experts
Lei Xu, Michael I. Jordan, Geoffrey E. Hinton
NIPS
1994
8 years 8 months ago
Using a neural net to instantiate a deformable model
Deformable models are an attractive approach to recognizing nonrigid objects which have considerable within class variability. However, there are severe search problems associated...
Christopher K. I. Williams, Michael Revow, Geoffre...
NIPS
1994
8 years 8 months ago
Morphogenesis of the Lateral Geniculate Nucleus: How Singularities Affect Global Structure
The macaque lateral geniculate nucleus (LGN) exhibits an intricate lamination pattern, which changes midway through the nucleus at a point coincident with small gaps due to the bl...
Svilen Tzonev, Klaus Schulten, Joseph G. Malpeli
NIPS
1994
8 years 8 months ago
Phase-Space Learning
In this paper, we present an improved version of the online phase-space learning algorithm of Tsung and Cottrell (1995), called ARTISTE (Autonomous Real-TIme Selection of Training...
Fu-Sheng Tsung, Garrison W. Cottrell
NIPS
1994
8 years 8 months ago
Combining Estimators Using Non-Constant Weighting Functions
This paper discusses the linearly weighted combination of estimators in which the weighting functions are dependent on the input. We show that the weighting functions can be deriv...
Volker Tresp, Michiaki Taniguchi
NIPS
1994
8 years 8 months ago
Efficient Methods for Dealing with Missing Data in Supervised Learning
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Volker Tresp, Ralph Neuneier, Subutai Ahmad
NIPS
1994
8 years 8 months ago
Finding Structure in Reinforcement Learning
Reinforcement learning addresses the problem of learning to select actions in order to maximize one's performance inunknownenvironments. Toscale reinforcement learning to com...
Sebastian Thrun, Anton Schwartz
NIPS
1994
8 years 8 months ago
Learning to Play the Game of Chess
This paper presents NeuroChess, a program which learns to play chess from the final outcome of games. NeuroChess learns chess board evaluation functions, represented by artificial...
Sebastian Thrun
books