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CEC
2010
IEEE
13 years 6 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
SSDBM
2007
IEEE
212views Database» more  SSDBM 2007»
14 years 1 months ago
Adaptive-Size Reservoir Sampling over Data Streams
Reservoir sampling is a well-known technique for sequential random sampling over data streams. Conventional reservoir sampling assumes a fixed-size reservoir. There are situation...
Mohammed Al-Kateb, Byung Suk Lee, Xiaoyang Sean Wa...
UAI
2000
13 years 8 months ago
Adaptive Importance Sampling for Estimation in Structured Domains
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
Luis E. Ortiz, Leslie Pack Kaelbling
GECCO
2004
Springer
118views Optimization» more  GECCO 2004»
14 years 25 days ago
Adaptive Sampling for Noisy Problems
Abstract. The usual approach to deal with noise present in many realworld optimization problems is to take an arbitrary number of samples of the objective function and use the samp...
Erick Cantú-Paz
GRAPHICSINTERFACE
2003
13 years 8 months ago
Entropy-based Adaptive Sampling
Ray tracing techniques need supersampling to reduce aliasing and/or noise in the final image. Since not all the pixels in the image require the same number of rays, supersampling...
Jaume Rigau, Miquel Feixas, Mateu Sbert