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» A Theory for Memory-Based Learning
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ADCM
2008
136views more  ADCM 2008»
15 years 6 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou
ERCIM
2008
130views more  ERCIM 2008»
15 years 6 months ago
Mediated Collaborative Learning
Information and Communication Technologies facilitate the emergence of new contexts and practices of learning that educational institutions have to adapt to their pedagogical disc...
Kostas Pentikousis, Carmen Martinez-Carrillo
TSMC
2008
146views more  TSMC 2008»
15 years 6 months ago
Decentralized Learning in Markov Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Peter Vrancx, Katja Verbeeck, Ann Nowé
169
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AI
2002
Springer
15 years 6 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
WWW
2009
ACM
16 years 6 months ago
Learning to tag
Social tagging provides valuable and crucial information for large-scale web image retrieval. It is ontology-free and easy to obtain; however, irrelevant tags frequently appear, a...
Lei Wu, Linjun Yang, Nenghai Yu, Xian-Sheng Hua