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» Localizing Search in Reinforcement Learning
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ESANN
2006
13 years 11 months ago
Diversity creation in local search for the evolution of neural network ensembles
Abstract. The EENCL algorithm [1] automatically designs neural network ensembles for classification, combining global evolution with local search based on gradient descent. Two mec...
Pete Duell, Iris Fermin, Xin Yao
BMCBI
2006
107views more  BMCBI 2006»
13 years 10 months ago
A reinforced merging methodology for mapping unique peptide motifs in members of protein families
Background: Members of a protein family often have highly conserved sequences; most of these sequences carry identical biological functions and possess similar three-dimensional (...
Hao-Teng Chang, Tun-Wen Pai, Tan-Chi Fan, Bo-Han S...
GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
13 years 12 months ago
Stochastic local search in continuous domains: questions to be answered when designing a novel algorithm
Several population-based methods (with origins in the world of evolutionary strategies and estimation-of-distribution algorithms) for black-box optimization in continuous domains ...
Petr Posik
AUSAI
2005
Springer
13 years 12 months ago
A Comparison of Evolutionary Methods for the Discovery of Local Search Heuristics
Abstract. Methods of adaptive constraint satisfaction have recently become of interest to overcome the limitations imposed on “black-box” search algorithms by the no free lunch...
Stuart Bain, John Thornton, Abdul Sattar
ICML
2010
IEEE
13 years 11 months ago
Feature Selection as a One-Player Game
This paper formalizes Feature Selection as a Reinforcement Learning problem, leading to a provably optimal though intractable selection policy. As a second contribution, this pape...
Romaric Gaudel, Michèle Sebag