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» Iterative Learning Control - Monotonicity and Optimization
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149
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CORR
2010
Springer
275views Education» more  CORR 2010»
15 years 2 months ago
Dictionary Optimization for Block-Sparse Representations
Recent work has demonstrated that using a carefully designed dictionary instead of a predefined one, can improve the sparsity in jointly representing a class of signals. This has m...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
129
Voted
GECCO
2008
Springer
118views Optimization» more  GECCO 2008»
15 years 3 months ago
Unsupervised learning of echo state networks: balancing the double pole
A possible alternative to fine topology tuning for Neural Network (NN) optimization is to use Echo State Networks (ESNs), recurrent NNs built upon a large reservoir of sparsely r...
Fei Jiang, Hugues Berry, Marc Schoenauer
139
Voted
CDC
2009
IEEE
285views Control Systems» more  CDC 2009»
15 years 13 days ago
Adaptive randomized algorithm for finding eigenvector of stochastic matrix with application to PageRank
Abstract-- The problem of finding the eigenvector corresponding to the largest eigenvalue of a stochastic matrix has numerous applications in ranking search results, multi-agent co...
Alexander V. Nazin, Boris T. Polyak
127
Voted
IJCNN
2006
IEEE
15 years 8 months ago
Reinforcement Learning Control for Biped Robot Walking on Uneven Surfaces
— Biped robots based on the concept of (passive) dynamic walking are far simpler than the traditional fullycontrolled walking robots, while achieving a more natural gait and cons...
Shouyi Wang, Jelmer Braaksma, Robert Babuska, Daan...
106
Voted
NIPS
1996
15 years 3 months ago
Reinforcement Learning for Mixed Open-loop and Closed-loop Control
Closed-loop control relies on sensory feedback that is usually assumed to be free. But if sensing incurs a cost, it may be coste ective to take sequences of actions in open-loop m...
Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstei...