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» SWAF: Swarm Algorithm Framework for Numerical Optimization
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ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
14 years 8 months ago
Reinforcement learning of motor skills in high dimensions: A path integral approach
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
91
Voted
ICASSP
2011
IEEE
14 years 1 months ago
OpenBliSSART: Design and evaluation of a research toolkit for Blind Source Separation in Audio Recognition Tasks
We describe and evaluate our toolkit openBliSSART (open-source Blind Source Separation for Audio Recognition Tasks), which is the C++ framework and toolbox that we have successful...
Felix Weninger, Alexander Lehmann, Björn Schu...
JMLR
2012
13 years 2 days ago
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
73
Voted
CDC
2008
IEEE
108views Control Systems» more  CDC 2008»
15 years 4 months ago
On the state-space design of optimal controllers for distributed systems with finite communication speed
— We consider the problem of designing optimal distributed controllers whose impulse response has limited propagation speed. We introduce a state-space framework in which such co...
Makan Fardad, Mihailo R. Jovanovic
AE
2005
Springer
15 years 3 months ago
Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies
Randomization is an efficient tool for global optimization. We here define a method which keeps : – the order 0 of evolutionary algorithms (no gradient) ; – the stochastic as...
Anne Auger, Mohamed Jebalia, Olivier Teytaud