1106 search results - page 85 / 222 » On regularization algorithms in learning theory |
187
Voted
TSP
2010
14 years 11 months ago
2010
We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimiz...
154
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ICML
2009
IEEE
16 years 5 months ago
2009
IEEE
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
126
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GECCO
2006
Springer
15 years 8 months ago
2006
Springer
Learning goal-scoring behaviour from scratch for simulated robot soccer is considered to be a very difficult problem, and is often achieved by endowing players with an innate set ...
177
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MCS
2005
Springer
15 years 10 months ago
2005
Springer
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
123
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SIGECOM
2009
ACM
15 years 11 months ago
2009
ACM
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...