PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Projected Equation Methods for Approximate Solution of Large Linear Systems
Dimitri Bertsekas and Huizhen Yu
Journal of Computational and Applied Mathematics Volume 227, Number 1, pp. 27-50, 2009.

Abstract

We consider linear systems of equations and solution approximations derived by projection on a low-dimensional subspace. We propose stochastic iterative algorithms, based on simulation, which converge to the approximate solution and are suitable for very large-dimensional problems. The algorithms are extensions of recent approximate dynamic programming methods, known as temporal difference methods, which solve a projected form of Bellman’s equation by using simulation-based approximations to this equation, or by using a projected value iteration method.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:3349
Deposited By:Huizhen Yu
Deposited On:08 February 2008