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NIPS
1993
8 years 9 months ago
Foraging in an Uncertain Environment Using Predictive Hebbian Learning
P. Read Montague, Peter Dayan, Terrence J. Sejnows...
NIPS
1993
8 years 9 months ago
Fast Pruning Using Principal Components
We present a new algorithm for eliminating excess parameters and improving network generalization after supervised training. The method, \Principal Components Pruning (PCP)",...
Asriel U. Levin, Todd K. Leen, John E. Moody
NIPS
1993
8 years 9 months ago
Optimal Stochastic Search and Adaptive Momentum
Stochastic optimization algorithms typically use learning rate schedules that behave asymptotically as (t) = 0=t. The ensemble dynamics (Leen and Moody, 1993) for such algorithms ...
Todd K. Leen, Genevieve B. Orr
NIPS
1993
8 years 9 months ago
Convergence of Stochastic Iterative Dynamic Programming Algorithms
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
NIPS
1993
8 years 9 months ago
Mixtures of Controllers for Jump Linear and Non-Linear Plants
We describe an extension to the Mixture of Experts architecture for modelling and controlling dynamical systems which exhibit multiple modesof behavior. This extension is based on...
Timothy W. Cacciatore, Steven J. Nowlan
NIPS
1993
8 years 9 months ago
Surface Learning with Applications to Lipreading
Most connectionist research has focused on learning mappings from one space to another (eg. classification and regression). This paper introduces the more general task of learnin...
Christoph Bregler, Stephen M. Omohundro
NIPS
1993
8 years 9 months ago
Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach
This paper describes the Q-routing algorithm for packet routing, in which a reinforcement learning module is embedded into each node of a switching network. Only local communicati...
Justin A. Boyan, Michael L. Littman
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