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SIAMCO
2002
71views more  SIAMCO 2002»
13 years 4 months ago
Rate of Convergence for Constrained Stochastic Approximation Algorithms
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
Robert Buche, Harold J. Kushner
CDC
2008
IEEE
148views Control Systems» more  CDC 2008»
13 years 11 months ago
Convergence rate for stochastic consensus algorithms with time-varying noise statistics: Asymptotic normality
— This paper studies consensus seeking over noisy networks with time-varying noise statistics. Stochastic approximation type algorithms can ensure consensus in mean square and wi...
Minyi Huang
ORL
2008
124views more  ORL 2008»
13 years 4 months ago
Sample average approximation of expected value constrained stochastic programs
We propose a sample average approximation (SAA) method for stochastic programming problems involving an expected value constraint. Such problems arise, for example, in portfolio s...
Wei Wang, Shabbir Ahmed
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
ML
2007
ACM
192views Machine Learning» more  ML 2007»
13 years 4 months ago
Annealing stochastic approximation Monte Carlo algorithm for neural network training
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
Faming Liang