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» A theory of learning from different domains
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FOIS
2006
14 years 11 months ago
Formalizing Ontology Alignment and its Operations with Category Theory
An ontology alignment is the expression of relations between different ontologies. In order to view alignments independently from the language expressing ontologies and from the te...
Antoine Zimmermann, Markus Krötzsch, Jé...
CP
2004
Springer
15 years 3 months ago
Heuristic Selection for Stochastic Search Optimization: Modeling Solution Quality by Extreme Value Theory
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
Vincent A. Cicirello, Stephen F. Smith
ICML
2004
IEEE
15 years 10 months ago
Learning to fly by combining reinforcement learning with behavioural cloning
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...
Eduardo F. Morales, Claude Sammut
IJCAI
1993
14 years 11 months ago
An Inductive Approach to Learning Search Control Rules for Planning
One method for reducing the time required for plan generation is to learn search control rules from experience. Most of the recent work in learning search control knowledge has co...
Christopher Leckie, Ingrid Zukerman
GECCO
2010
Springer
169views Optimization» more  GECCO 2010»
14 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