Sciweavers

424 search results - page 15 / 85
» Boosted sampling: approximation algorithms for stochastic op...
Sort
View
NIPS
2004
13 years 8 months ago
The Convergence of Contrastive Divergences
This paper analyses the Contrastive Divergence algorithm for learning statistical parameters. We relate the algorithm to the stochastic approximation literature. This enables us t...
Alan L. Yuille
ICML
2000
IEEE
14 years 8 months ago
Reinforcement Learning in POMDP's via Direct Gradient Ascent
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
Jonathan Baxter, Peter L. Bartlett
FOCS
2004
IEEE
13 years 11 months ago
Stochastic Optimization is (Almost) as easy as Deterministic Optimization
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
David B. Shmoys, Chaitanya Swamy
UAI
2001
13 years 8 months ago
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
John D. Lafferty, Larry A. Wasserman
WSC
2004
13 years 8 months ago
Experimental Performance Evaluation of Histogram Approximation for Simulation Output Analysis
We summarize the results of an experimental performance evaluation of using an empirical histogram to approximate the steady-state distribution of the underlying stochastic proces...
E. Jack Chen, W. David Kelton