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ATAL
2005
Springer
14 years 26 days ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Motif kernel generated by genetic programming improves remote homology and fold detection
Background: Protein remote homology detection is a central problem in computational biology. Most recent methods train support vector machines to discriminate between related and ...
Tony Håndstad, Arne J. H. Hestnes, Pål...
IMSCCS
2007
IEEE
14 years 1 months ago
Asymmetric Bagging and Feature Selection for Activities Prediction of Drug Molecules
Background: Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cy...
Guo-Zheng Li, Hao-Hua Meng, Mary Qu Yang, Jack Y. ...
PPSC
1989
13 years 8 months ago
Evaluating Block Algorithm Variants in LAPACK
The LAPACK software project currently under development is intended to provide a portable linear algebra library for high performance computers. LAPACK will make use of the Level 1...
Ed Anderson, Jack Dongarra
NIPS
2008
13 years 8 months ago
Optimization on a Budget: A Reinforcement Learning Approach
Many popular optimization algorithms, like the Levenberg-Marquardt algorithm (LMA), use heuristic-based "controllers" that modulate the behavior of the optimizer during ...
Paul Ruvolo, Ian R. Fasel, Javier R. Movellan