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NIPS
2001
15 years 5 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr
UAI
2004
15 years 5 months ago
On the Choice of Regions for Generalized Belief Propagation
Generalized belief propagation (GBP) has proven to be a promising technique for approximate inference tasks in AI and machine learning. However, the choice of a good set of cluste...
Max Welling
AAAI
1998
15 years 5 months ago
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Adam J. Grove, Dale Schuurmans
AAAI
2000
15 years 5 months ago
Deliberation in Equilibrium: Bargaining in Computationally Complex Problems
We develop a normative theory of interaction-negotiation in particular--among self-interested computationally limited agents where computational actions are game-theoretically tre...
Kate Larson, Tuomas Sandholm
SGP
2003
15 years 5 months ago
Explicit Surface Remeshing
We present a new remeshing scheme based on the idea of improving mesh quality by a series of local modifications of the mesh geometry and connectivity. Our contribution to the fa...
Vitaly Surazhsky, Craig Gotsman