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COLT
1993
Springer
15 years 7 months ago
1993
Springer
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
143
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PERVASIVE
2011
Springer
14 years 6 months ago
2011
Springer
We contribute a method for approximating users’ interruptibility costs to use for experience sampling and validate the method in an application that learns when to automatically ...
143
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NIPS
2003
15 years 5 months ago
2003
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
143
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ICONIP
2007
15 years 5 months ago
2007
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
151
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Publication
Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...