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» Expected Convergence Properties of BGP
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WSC
2001
13 years 9 months ago
On improving the performance of simulation-based algorithms for average reward processes with application to network pricing
We address performance issues associated with simulationbased algorithms for optimizing Markov reward processes. Specifically, we are concerned with algorithms that exploit the re...
Enrique Campos-Náñez, Stephen D. Pat...
AAAI
1998
13 years 9 months ago
Bayesian Q-Learning
A central problem in learning in complex environmentsis balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of explora...
Richard Dearden, Nir Friedman, Stuart J. Russell
CORR
2010
Springer
136views Education» more  CORR 2010»
13 years 4 months ago
Comparing Prediction Market Structures, With an Application to Market Making
Ensuring sufficient liquidity is one of the key challenges for designers of prediction markets. Various market making algorithms have been proposed in the literature and deployed ...
Aseem Brahma, Sanmay Das, Malik Magdon-Ismail
TOMACS
2010
79views more  TOMACS 2010»
13 years 2 months ago
A stochastic approximation method with max-norm projections and its applications to the Q-learning algorithm
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...
Sumit Kunnumkal, Huseyin Topaloglu
ICML
2004
IEEE
14 years 8 months ago
Leveraging the margin more carefully
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...
Nir Krause, Yoram Singer