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NIPS
2001
14 years 9 days ago
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
Gregory Z. Grudic, Lyle H. Ungar
CAGD
2007
65views more  CAGD 2007»
13 years 11 months ago
Progressive iterative approximation and bases with the fastest convergence rates
All normalized totally positive bases satisfy the progressive iterative approximation property. The normalized B-basis has optimal shape preserving properties and we prove that it...
Jorge Delgado, Juan Manuel Peña
CORR
2008
Springer
107views Education» more  CORR 2008»
13 years 11 months ago
Randomized Methods for Linear Constraints: Convergence Rates and Conditioning
We study randomized variants of two classical algorithms: coordinate descent for systems of linear equations and iterated projections for systems of linear inequalities. Expanding...
D. Leventhal, A. S. Lewis
ICASSP
2008
IEEE
14 years 5 months ago
Distributed average consensus with increased convergence rate
The average consensus problem in the distributed signal processing context is addressed by linear iterative algorithms, with asymptotic convergence to the consensus. The convergen...
Boris N. Oreshkin, Tuncer C. Aysal, Mark Coates
SIAMNUM
2010
131views more  SIAMNUM 2010»
13 years 5 months ago
A Rational Interpolation Scheme with Superpolynomial Rate of Convergence
The purpose of this study is to construct a high-order interpolation scheme for arbitrary scattered datasets. The resulting function approximation is an interpolation function when...
Qiqi Wang, Parviz Moin, Gianluca Iaccarino