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PRL
2006
117views more  PRL 2006»
14 years 11 months ago
Feature selection in robust clustering based on Laplace mixture
A wrapped feature selection process is proposed in the context of robust clustering based on Laplace mixture models. The clustering approach we consider is a generalization of the...
Aurélien Cord, Christophe Ambroise, Jean Pi...
GECCO
2010
Springer
237views Optimization» more  GECCO 2010»
15 years 4 months ago
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noiseless BBOB-2010 testbed
The well-known Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a robust stochastic search algorithm for optimizing functions defined on a continuous search space RD ....
Anne Auger, Dimo Brockhoff, Nikolaus Hansen
CIKM
2010
Springer
14 years 10 months ago
A unified optimization framework for robust pseudo-relevance feedback algorithms
We present a flexible new optimization framework for finding effective, reliable pseudo-relevance feedback models that unifies existing complementary approaches in a principled wa...
Joshua V. Dillon, Kevyn Collins-Thompson
SIAMFM
2011
72views more  SIAMFM 2011»
14 years 2 months ago
Robust Hedging of Double Touch Barrier Options
We consider model-free pricing of digital options, which pay out if the underlying asset has crossed both upper and lower barriers. We make only weak assumptions about the underly...
A. M. G. Cox, Jan Obloj
GECCO
2004
Springer
15 years 5 months ago
The Lens Design Using the CMA-ES Algorithm
This paper presents a lens system design algorithm using the covariance matrix adaptation evolution strategy (CMA-ES), which is one of the most powerful self-adaptation mechanisms....
Yuichi Nagata