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» Solving Hierarchical Optimization Problems Using MOEAs
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110
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SEMWEB
2010
Springer
14 years 10 months ago
Preference-Based Web Service Composition: A Middle Ground between Execution and Search
Abstract. Much of the research on automated Web Service Composition (WSC) relates it to an AI planning task, where the composition is primarily done offline prior to execution. Rec...
Shirin Sohrabi, Sheila A. McIlraith
115
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LION
2007
Springer
192views Optimization» more  LION 2007»
15 years 6 months ago
Learning While Optimizing an Unknown Fitness Surface
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Roberto Battiti, Mauro Brunato, Paolo Campigotto
GECCO
2005
Springer
101views Optimization» more  GECCO 2005»
15 years 6 months ago
A scalable parallel genetic algorithm for x-ray spectroscopic analysis
We use a parallel multi-objective genetic algorithm to drive a search and reconstruction spectroscopic analysis of plasma gradients in inertial confinement fusion (ICF) implosion...
Kai Xu, Sushil J. Louis, Roberto C. Mancini
NIPS
2007
15 years 2 months ago
Multi-Task Learning via Conic Programming
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, ...
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
15 years 2 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang