424 search results - page 23 / 85 » Boosted sampling: approximation algorithms for stochastic op... |
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
SODA
2010
ACM
14 years 4 months ago
2010
ACM
We consider a robust model proposed by Scarf, 1958, for stochastic optimization when only the marginal probabilities of (binary) random variables are given, and the correlation be...
NLP
2000
13 years 11 months ago
2000
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...
CCE
2004
13 years 7 months ago
2004
A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncer...
SAGA
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Motivated by an application in project portfolio analysis under uncertainty, we develop an algorithm S-VNS for solving stochastic combinatorial optimization (SCO) problem...