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NIPS
1993
15 years 7 months ago
Convergence of Stochastic Iterative Dynamic Programming Algorithms
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
CSSE
2008
IEEE
16 years 25 days ago
Stochastic Gradient Algorithm for Multi-input Systems Based on the Auxiliary Model
—This paper presents an auxiliary model based stochastic gradient parameter estimation algorithm for multiinput output-error systems by minimizing a quadratic cost function. The ...
Yuwu Liao, Xianfang Wang, Rui Feng Ding
SIAMCO
2002
71views more  SIAMCO 2002»
15 years 6 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
SAINT
2005
IEEE
15 years 12 months ago
A Matrix Pattern Compliant Strong Stochastic Bound
Stochastic bounds are a promising method to analyze QoS requirements. Indeed it is sufficient to prove that a bound of the real performance satisfies the guarantee. However, the...
Ana Busic, Jean-Michel Fourneau