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TIP
2008
89views more  TIP 2008»
14 years 9 months ago
Optimal Denoising in Redundant Representations
Abstract--Image denoising methods are often designed to minimize mean-squared error (MSE) within the subbands of a multiscale decomposition. However, most high-quality denoising re...
Martin Raphan, Eero P. Simoncelli
CEC
2010
IEEE
14 years 11 months ago
Constrained global optimization of low-thrust interplanetary trajectories
The optimization of spacecraft trajectories can be formulated as a global optimization task. The complexity of the problem depends greatly on the problem formulation, on the spacec...
Chit Hong Yam, David Di Lorenzo, Dario Izzo
ICML
2001
IEEE
15 years 10 months ago
Direct Policy Search using Paired Statistical Tests
Direct policy search is a practical way to solve reinforcement learning problems involving continuous state and action spaces. The goal becomes finding policy parameters that maxi...
Malcolm J. A. Strens, Andrew W. Moore
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
15 years 4 months ago
Self-adaptive ant colony optimisation applied to function allocation in vehicle networks
Modern vehicles possess an increasing number of software and hardware components that are integrated in electronic control units (ECUs). Finding an optimal allocation for all comp...
Manuel Förster, Bettina Bickel, Bernd Hardung...
GECCO
2009
Springer
141views Optimization» more  GECCO 2009»
15 years 4 months ago
Distributed hyper-heuristics for real parameter optimization
Hyper-heuristics (HHs) are heuristics that work with an arbitrary set of search operators or algorithms and combine these algorithms adaptively to achieve a better performance tha...
Marco Biazzini, Balázs Bánhelyi, Alb...