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GECCO
2004
Springer
16 years 17 days ago
Bounding Learning Time in XCS
It has been shown empirically that the XCS classifier system solves typical classification problems in a machine learning competitive way. However, until now, no learning time es...
Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
GECCO
2004
Springer
122views Optimization» more  GECCO 2004»
16 years 17 days ago
Gradient-Based Learning Updates Improve XCS Performance in Multistep Problems
This paper introduces a gradient-based reward prediction update mechanism to the XCS classifier system as applied in neuralnetwork type learning and function approximation mechani...
Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
GECCO
2004
Springer
150views Optimization» more  GECCO 2004»
16 years 17 days ago
Parameter Adaptation within Co-adaptive Learning Classifier Systems
The authors propose a co-adaptive approach to controlling parameters for coevolution-based learning classifier systems. By taking advantage of the on-line incremental learning capa...
Chung-Yuan Huang, Chuen-Tsai Sun
COLT
2003
Springer
16 years 12 days ago
Preference Elicitation and Query Learning
Abstract. In this paper we initiate an exploration of relationships between “preference elicitation”, a learning-style problem that arises in combinatorial auctions, and the pr...
Avrim Blum, Jeffrey C. Jackson, Tuomas Sandholm, M...
ICASSP
2011
IEEE
14 years 11 months ago
Maximum margin structure learning of Bayesian network classifiers
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
Franz Pernkop, Michael Wohlmay, Manfred Mücke