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CVPR
2010
IEEE
12 years 2 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
IPCO
2004
144views Optimization» more  IPCO 2004»
13 years 6 months ago
Hedging Uncertainty: Approximation Algorithms for Stochastic Optimization Problems
Abstract. We study two-stage, finite-scenario stochastic versions of several combinatorial optimization problems, and provide nearly tight approximation algorithms for them. Our pr...
R. Ravi, Amitabh Sinha
WSC
2001
13 years 6 months ago
Global random optimization by simultaneous perturbation stochastic approximation
We examine the theoretical and numerical global convergence properties of a certain "gradient free" stochastic approximation algorithm called the "simultaneous pertu...
John L. Maryak, Daniel C. Chin
INFOCOM
1998
IEEE
13 years 9 months ago
A Stochastic Approximation Approach for Max-Min Fair Adaptive Rate Control of ABR Sessions with MCRs
The ABR sessions in an ATM network share the bandwidth left over after guaranteeing service to CBR and VBR traffic. Hence the bandwidth available to ABR sessions is randomly varyi...
Santosh Paul Abraham, Anurag Kumar
SIAMCO
2000
117views more  SIAMCO 2000»
13 years 4 months ago
The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
Vivek S. Borkar, Sean P. Meyn