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SIAMCO
2002
71views more  SIAMCO 2002»
15 years 5 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
DCOSS
2011
Springer
14 years 5 months ago
A local average consensus algorithm for wireless sensor networks
—In many application scenarios sensors need to calculate the average of some local values, e.g. of local measurements. A possible solution is to rely on consensus algorithms. In ...
Konstantin Avrachenkov, Mahmoud El Chamie, Giovann...
CORR
2010
Springer
107views Education» more  CORR 2010»
15 years 4 months ago
Distributed Detection over Time Varying Networks: Large Deviations Analysis
—We apply large deviations theory to study asymptotic performance of running consensus distributed detection in sensor networks. Running consensus is a stochastic approximation t...
Dragana Bajovic, Dusan Jakovetic, João Xavi...
QUESTA
2006
61views more  QUESTA 2006»
15 years 6 months ago
Convergence rates in monotone separable stochastic networks
Serguei Foss, Artëm Sapozhnikov
ML
2007
ACM
192views Machine Learning» more  ML 2007»
15 years 5 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