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181
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SAC
2008
ACM
15 years 4 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
JMLR
2010
145views more  JMLR 2010»
14 years 11 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
MFCS
2009
Springer
15 years 9 months ago
Sampling Edge Covers in 3-Regular Graphs
An edge cover C of an undirected graph is a set of edges such that every vertex has an adjacent edge in C. We show that a Glauber dynamics Markov chain for edge covers mixes rapidl...
Ivona Bezáková, William A. Rummler
119
Voted
WSC
2004
15 years 6 months ago
Optimal Computing Budget Allocation Under Correlated Sampling
We consider the optimal computing budget allocation (OCBA) problem where the simulated designs are correlated. The exact optimal allocation is presented for two designs, and an ap...
Michael C. Fu, Jian-Qiang Hu, Chun-Hung Chen, Xiao...
WSCG
2003
154views more  WSCG 2003»
15 years 6 months ago
Direction Fields over Point-Sampled Geometry
We describe techniques to establish local frames over point-sampled manifold surfaces. The tangential alignment of local frames is determined using a wave front algorithm starting...
Marc Alexa, Tobias Klug, Carsten Stoll