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KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 3 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
GECCO
2010
Springer
237views Optimization» more  GECCO 2010»
15 years 8 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
149
Voted
GECCO
2010
Springer
187views Optimization» more  GECCO 2010»
15 years 7 months ago
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noisy BBOB-2010 testbed
The Covariance-Matrix-Adaptation Evolution-Strategy (CMA-ES) is a robust stochastic search algorithm for optimizing functions defined on a continuous search space RD . Recently, ...
Anne Auger, Dimo Brockhoff, Nikolaus Hansen
131
Voted
CEC
2010
IEEE
15 years 2 months ago
Gaussian Adaptation as a unifying framework for continuous black-box optimization and adaptive Monte Carlo sampling
Abstract— We present a unifying framework for continuous optimization and sampling. This framework is based on Gaussian Adaptation (GaA), a search heuristic developed in the late...
Christian L. Müller, Ivo F. Sbalzarini
127
Voted
SGP
2003
15 years 4 months ago
Provably Good Surface Sampling and Approximation
We present an algorithm for meshing surfaces that is a simple adaptation of a greedy “farthest point” technique proposed by Chew. Given a surface S, it progressively adds poin...
Steve Oudot, Jean-Daniel Boissonnat