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STOC
2009
ACM
14 years 8 months ago
2009
ACM
The low-rank matrix approximation problem involves finding of a rank k version of a m ? n matrix AAA, labeled AAAk, such that AAAk is as "close" as possible to the best ...
SLS
2009
Springer
14 years 2 months ago
2009
Springer
Stochastic local search algorithms can now successfully solve MAXSAT problems with thousands of variables or more. A key to this success is how effectively the search can navigate...
CP
1998
Springer
14 years 2 days ago
1998
Springer
A well-studied problem in the electric power industry is that of optimally scheduling preventative maintenance of power generating units within a power plant. We show how these pr...
CORR
2010
Springer
13 years 8 months ago
2010
Springer
During the last decade, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs), have been shown to work well in practice and to po...
ESA
2008
Springer
13 years 9 months ago
2008
Springer
The focus is on black-box optimization of a function f : RN R given as a black box, i. e. an oracle for f-evaluations. This is commonly called direct search, and in fact, most meth...