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» Sequential sampling for solving stochastic programs
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ICASSP
2008
IEEE
14 years 1 months ago
Compressed sensing with sequential observations
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of measurements. The results in the literature have focuse...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
UAI
2004
13 years 8 months ago
Bidding under Uncertainty: Theory and Experiments
This paper describes a study of agent bidding strategies, assuming combinatorial valuations for complementary and substitutable goods, in three auction environments: sequential au...
Amy R. Greenwald, Justin A. Boyan
ICCAD
2007
IEEE
96views Hardware» more  ICCAD 2007»
14 years 4 months ago
Monte-Carlo driven stochastic optimization framework for handling fabrication variability
Increasing effects of fabrication variability have inspired a growing interest in statistical techniques for design optimization. In this work, we propose a Monte-Carlo driven sto...
Vishal Khandelwal, Ankur Srivastava
ECAI
2010
Springer
13 years 8 months ago
EP for Efficient Stochastic Control with Obstacles
Abstract. We address the problem of continuous stochastic optimal control in the presence of hard obstacles. Due to the non-smooth character of the obstacles, the traditional appro...
Thomas Mensink, Jakob J. Verbeek, Bert Kappen
PPOPP
2005
ACM
14 years 29 days ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...