311 search results - page 15 / 63 » Gradient Convergence in Gradient methods with Errors |
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
NIPS
2001
13 years 9 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
EOR
2007
13 years 7 months ago
2007
A simultaneous perturbation stochastic approximation (SPSA) method has been developed in this paper, using the operators of perturbation with the Lipschitz density function. This ...
TVCG
2011
13 years 2 months ago
2011
—In this paper, we present two methods for accurate gradient estimation from scalar field data sampled on regular lattices. The first method is based on the multidimensional Tayl...
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
This paper introduces a new method to maximize kurtosisbased contrast functions. Such contrast functions appear in the problem of blind source separation of convolutively mixed so...