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NIPS
2003
15 years 3 months ago
Perspectives on Sparse Bayesian Learning
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
David P. Wipf, Jason A. Palmer, Bhaskar D. Rao
CCIA
2005
Springer
15 years 7 months ago
Direct Policy Search Reinforcement Learning for Robot Control
— This paper proposes a high-level Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, whe...
Andres El-Fakdi, Marc Carreras, Narcís Palo...
GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
15 years 3 months ago
Hierarchical evolution of linear regressors
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
Francesc Teixidó-Navarro, Albert Orriols-Pu...
COLT
1993
Springer
15 years 6 months ago
Learning from a Population of Hypotheses
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
Michael J. Kearns, H. Sebastian Seung
UAI
2008
15 years 3 months ago
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
We consider the problem of efficiently learning optimal control policies and value functions over large state spaces in an online setting in which estimates must be available afte...
Richard S. Sutton, Csaba Szepesvári, Alborz...