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» A branch and bound method for stochastic global optimization
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UAI
2001
14 years 11 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
78
Voted
NIPS
2001
14 years 11 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
ACCV
2009
Springer
15 years 4 months ago
Highly-Automatic MI Based Multiple 2D/3D Image Registration Using Self-initialized Geodesic Feature Correspondences
Abstract. Intensity based registration methods, such as the mutual information (MI), do not commonly consider the spatial geometric information and the initial correspondences are ...
Hongwei Zheng, Ioan Cleju, Dietmar Saupe
128
Voted
ICDAR
2009
IEEE
14 years 7 months ago
Unconstrained Handwritten Document Layout Extraction Using 2D Conditional Random Fields
The paper describes a new approach using a Conditional Random Fields (CRFs) to extract physical and logical layouts in unconstrained handwritten letters such as those sent by indi...
Florent Montreuil, Emmanuele Grosicki, Laurent Heu...
ATAL
2003
Springer
15 years 2 months ago
Optimizing information exchange in cooperative multi-agent systems
Decentralized control of a cooperative multi-agent system is the problem faced by multiple decision-makers that share a common set of objectives. The decision-makers may be robots...
Claudia V. Goldman, Shlomo Zilberstein