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» TRUST-TECH based Methods for Optimization and Learning
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SEMWEB
2005
Springer
15 years 6 months ago
Bootstrapping Ontology Alignment Methods with APFEL
Abstract. Ontology alignment is a prerequisite in order to allow for interoperation between different ontologies and many alignment strategies have been proposed to facilitate the ...
Marc Ehrig, Steffen Staab, York Sure
ICML
1997
IEEE
16 years 1 months ago
Hierarchical Explanation-Based Reinforcement Learning
Explanation-Based Reinforcement Learning (EBRL) was introduced by Dietterich and Flann as a way of combining the ability of Reinforcement Learning (RL) to learn optimal plans with...
Prasad Tadepalli, Thomas G. Dietterich
AIPS
2008
15 years 2 months ago
An Online Learning Method for Improving Over-Subscription Planning
Despite the recent resurgence of interest in learning methods for planning, most such efforts are still focused exclusively on classical planning problems. In this work, we invest...
Sung Wook Yoon, J. Benton, Subbarao Kambhampati
176
Voted
IC3
2010
15 years 23 days ago
LACAIS: Learning Automata Based Cooperative Artificial Immune System for Function Optimization
Artificial Immune System (AIS) is taken into account from evolutionary algorithms that have been inspired from defensive mechanism of complex natural immune system. For using this ...
Alireza Rezvanian, Mohammad Reza Meybodi
82
Voted
ICML
2003
IEEE
16 years 1 months ago
Adaptive Overrelaxed Bound Optimization Methods
We study a class of overrelaxed bound optimization algorithms, and their relationship to standard bound optimizers, such as ExpectationMaximization, Iterative Scaling, CCCP and No...
Ruslan Salakhutdinov, Sam T. Roweis