248 search results - page 19 / 50 » Rate of Convergence for Constrained Stochastic Approximation... |
115
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JAT
2010
15 years 1 months ago
2010
A common problem in applied mathematics is that of finding a function in a Hilbert space with prescribed best approximations from a finite number of closed vector subspaces. In ...
114
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WSC
2008
15 years 5 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
121
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JAT
2006
15 years 3 months ago
2006
Opposed to linear schemes, nonlinear function approximation allows to obtain a dimension independent rate of convergence. Unfortunately, in the presence of data noise typical algo...
134
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TNN
1998
15 years 3 months ago
1998
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
132
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NIPS
2007
15 years 4 months ago
2007
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...