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126
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ALT
2006
Springer
16 years 19 days ago
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
Daniil Ryabko, Marcus Hutter
134
Voted
JDCTA
2010
160views more  JDCTA 2010»
14 years 10 months ago
Learning and Decision Making in Human During a Game of Matching Pennies
To gain insights into the neural basis of such adaptive decision-making processes, we investigated the nature of learning process in humans playing a competitive game with binary ...
Jianfeng Hu, Xiaofeng Li, Jinghai Yin
117
Voted
ICIP
2003
IEEE
16 years 5 months ago
Sparse decompositions in "incoherent" dictionaries
The purpose of this paper is to generalize a result by Donoho, Huo, Elad and Bruckstein on sparse representations of signals/images in a union of two orthonormal bases. We conside...
Morten Nielsen, Rémi Gribonval
114
Voted
ICASSP
2010
IEEE
15 years 3 months ago
Learning sparse systems at sub-Nyquist rates: A frequency-domain approach
We propose a novel algorithm for sparse system identification in the frequency domain. Key to our result is the observation that the Fourier transform of the sparse impulse respo...
Martin McCormick, Yue M. Lu, Martin Vetterli
121
Voted
ICIP
2006
IEEE
16 years 5 months ago
Tree-Based Orthogonal Matching Pursuit Algorithm for Signal Reconstruction
Recent studies in linear inverse problems have recognized the sparse representation of unknown signal in a certain basis as an useful and effective prior information to solve thos...
Chinh La, Minh N. Do