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» On Learning with Integral Operators
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ICML
2010
IEEE
15 years 7 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
IJRR
2008
186views more  IJRR 2008»
15 years 6 months ago
Automated Design of Adaptive Controllers for Modular Robots using Reinforcement Learning
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
Paulina Varshavskaya, Leslie Pack Kaelbling, Danie...
COGSCI
2004
106views more  COGSCI 2004»
15 years 6 months ago
Can musical transformations be implicitly learned?
The dominant theory of what people can learn implicitly is that they learn chunks of adjacent elements in sequences. A type of musical grammar that goes beyond specifying allowabl...
Zoltan Dienes, H. Christopher Longuet-Higgins
JMLR
2002
125views more  JMLR 2002»
15 years 6 months ago
Lyapunov Design for Safe Reinforcement Learning
Lyapunov design methods are used widely in control engineering to design controllers that achieve qualitative objectives, such as stabilizing a system or maintaining a system'...
Theodore J. Perkins, Andrew G. Barto
ICASSP
2011
IEEE
14 years 10 months ago
Social norm and long-run learning in peer-to-peer networks
We start by formulating the resource sharing in peer-to-peer (P2P) networks as a random-matching gift-giving game, where self-interested peers aim at maximizing their own long-ter...
Yu Zhang, Mihaela van der Schaar