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» A Guided Monte Carlo Approach to Optimization Problems
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ASPDAC
2000
ACM
154views Hardware» more  ASPDAC 2000»
13 years 11 months ago
Dynamic weighting Monte Carlo for constrained floorplan designs in mixed signal application
Simulated annealing has been one of the most popular stochastic optimization methods used in the VLSI CAD field in the past two decades for handling NP-hard optimization problems...
Jason Cong, Tianming Kong, Faming Liang, Jun S. Li...
MP
2008
117views more  MP 2008»
13 years 7 months ago
Stochastic programming approach to optimization under uncertainty
In this paper we discuss computational complexity and risk averse approaches to two and multistage stochastic programming problems. We argue that two stage (say linear) stochastic ...
Alexander Shapiro
AIPS
2009
13 years 8 months ago
Lower Bounding Klondike Solitaire with Monte-Carlo Planning
Despite its ubiquitous presence, very little is known about the odds of winning the simple card game of Klondike Solitaire. The main goal of this paper is to investigate the use o...
Ronald Bjarnason, Alan Fern, Prasad Tadepalli
AMDO
2008
Springer
13 years 9 months ago
Inverse Kinematics Using Sequential Monte Carlo Methods
Abstract. In this paper we propose an original approach to solve the Inverse Kinematics problem. Our framework is based on Sequential Monte Carlo Methods and has the advantage to a...
Nicolas Courty, Elise Arnaud
VLSISP
2002
123views more  VLSISP 2002»
13 years 7 months ago
Monte Carlo Bayesian Signal Processing for Wireless Communications
Abstract. Many statistical signal processing problems found in wireless communications involves making inference about the transmitted information data based on the received signal...
Xiaodong Wang, Rong Chen, Jun S. Liu