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» Global Optimization for Value Function Approximation
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ICCV
2009
IEEE
15 years 1 months ago
Extending Continuous Cuts: Anisotropic Metrics and Expansion Moves
The concept of graph cuts is by now a standard method for all sorts of low level vision problems. Its popularity is largely due to the fact that globally or near globally optimal...
Carl Olsson, Martin Byr¨od, Niels Chr. Overgaard,...
NIPS
1998
13 years 10 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
ICML
2006
IEEE
14 years 9 months ago
Fast direct policy evaluation using multiscale analysis of Markov diffusion processes
Policy evaluation is a critical step in the approximate solution of large Markov decision processes (MDPs), typically requiring O(|S|3 ) to directly solve the Bellman system of |S...
Mauro Maggioni, Sridhar Mahadevan
UAI
2008
13 years 10 months ago
Observation Subset Selection as Local Compilation of Performance Profiles
Deciding what to sense is a crucial task, made harder by dependencies and by a nonadditive utility function. We develop approximation algorithms for selecting an optimal set of me...
Yan Radovilsky, Solomon Eyal Shimony
NIPS
2007
13 years 10 months ago
Convex Clustering with Exemplar-Based Models
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Danial Lashkari, Polina Golland