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» On Using Monte Carlo Methods for Scheduling
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SAC
2008
ACM
13 years 7 months ago
Adaptive methods for sequential importance sampling with application to state space models
Abstract. In this paper we discuss new adaptive proposal strategies for sequential Monte Carlo algorithms--also known as particle filters--relying on new criteria evaluating the qu...
Julien Cornebise, Eric Moulines, Jimmy Olsson
NIPS
2007
13 years 9 months ago
Markov Chain Monte Carlo with People
Many formal models of cognition implicitly use subjective probability distributions to capture the assumptions of human learners. Most applications of these models determine these...
Adam Sanborn, Thomas L. Griffiths
RC
2007
78views more  RC 2007»
13 years 7 months ago
Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Potential Engineering Applications
Abstract. In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineering, statistical methods are used, methods assuming that we know the p...
Vladik Kreinovich, Jan Beck, Carlos Ferregut, Arac...
DATE
2010
IEEE
119views Hardware» more  DATE 2010»
13 years 7 months ago
Practical Monte-Carlo based timing yield estimation of digital circuits
—The advanced sampling and variance reduction techniques as efficient alternatives to the slow crude-MC method have recently been adopted for the analysis of timing yield in dig...
Javid Jaffari, Mohab Anis
PR
2011
12 years 10 months ago
Generalized darting Monte Carlo
One of the main shortcomings of Markov chain Monte Carlo samplers is their inability to mix between modes of the target distribution. In this paper we show that advance knowledge ...
Cristian Sminchisescu, Max Welling