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ICASSP
2008
IEEE
14 years 7 days ago
A new Particle Filtering algorithm with structurally optimal importance function
Bayesian estimation in nonlinear stochastic dynamical systems has been addressed for a long time. Among other solutions, Particle Filtering (PF) algorithms propagate in time a Mon...
Boujemaa Ait-El-Fquih, François Desbouvries
RT
2005
Springer
13 years 11 months ago
Importance Resampling for Global Illumination
This paper develops importance resampling into a variance reduction technique for Monte Carlo integration. Importance resampling is a sample generation technique that can be used ...
Justin Talbot, David Cline, Parris K. Egbert
AAAI
2007
13 years 8 months ago
Approximate Counting by Sampling the Backtrack-free Search Space
We present a new estimator for counting the number of solutions of a Boolean satisfiability problem as a part of an importance sampling framework. The estimator uses the recently...
Vibhav Gogate, Rina Dechter
FOCS
2006
IEEE
13 years 12 months ago
Fast Algorithms for Logconcave Functions: Sampling, Rounding, Integration and Optimization
We prove that the hit-and-run random walk is rapidly mixing for an arbitrary logconcave distribution starting from any point in the support. This extends the work of [26], where t...
László Lovász, Santosh Vempal...
ICRA
1995
IEEE
188views Robotics» more  ICRA 1995»
13 years 9 months ago
Fast Approximation of Range Images by Triangular Meshes Generated through Adaptive Randomized Sampling
This paper describes and evaluates an efficient technique that allows the fast generation of 3D triangular meshes from range images avoiding optimization procedures. Such a tool ...
Miguel Angel García