21 search results - page 1 / 5 » A stochastic approximation method with max-norm projections ... |
TOMACS
2010
12 years 11 months ago
2010
In this paper, we develop a stochastic approximation method to solve a monotone estimation problem and use this method to enhance the empirical performance of the Q-learning algor...
NIPS
2008
13 years 6 months ago
2008
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
CPAIOR
2008
Springer
13 years 6 months ago
2008
Springer
The one-step anticipatory algorithm (1s-AA) is an online algorithm making decisions under uncertainty by ignoring future non-anticipativity constraints. It makes near-optimal decis...
ACL
2009
13 years 2 months ago
2009
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
CDC
2010
IEEE
12 years 11 months ago
2010
IEEE
Abstract-- In this paper, we consider the distributed computation of equilibria arising in monotone stochastic Nash games over continuous strategy sets. Such games arise in setting...