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GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
14 years 3 months ago
Reducing the space-time complexity of the CMA-ES
A limited memory version of the covariance matrix adaptation evolution strategy (CMA-ES) is presented. This algorithm, L-CMA-ES, improves the space and time complexity of the CMA-...
James N. Knight, Monte Lunacek
MP
2006
87views more  MP 2006»
13 years 9 months ago
Convexity and decomposition of mean-risk stochastic programs
Abstract. Traditional stochastic programming is risk neutral in the sense that it is concerned with the optimization of an expectation criterion. A common approach to addressing ri...
Shabbir Ahmed
SIGMOD
2011
ACM
269views Database» more  SIGMOD 2011»
13 years 1 days ago
Advancing data clustering via projective clustering ensembles
Projective Clustering Ensembles (PCE) are a very recent advance in data clustering research which combines the two powerful tools of clustering ensembles and projective clustering...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...
VRCAI
2004
ACM
14 years 2 months ago
Explorative construction of virtual worlds: an interactive kernel approach
Despite steady research advances in many aspects of virtual reality, building and testing virtual worlds remains to be a very difficult process. Most virtual environments are stil...
Jinseok Seo, Gerard Jounghyun Kim
SIAMJO
2010
83views more  SIAMJO 2010»
13 years 7 months ago
The Lifted Newton Method and Its Application in Optimization
Abstract. We present a new “lifting” approach for the solution of nonlinear optimization problems (NLPs) that have objective and constraint functions with intermediate variable...
Jan Albersmeyer, Moritz Diehl