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» On Unbiased Linear Approximations
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83
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ICML
2009
IEEE
16 years 1 months ago
Constraint relaxation in approximate linear programs
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
Marek Petrik, Shlomo Zilberstein
VMV
2003
154views Visualization» more  VMV 2003»
15 years 1 months ago
Piecewise Linear Approximation of Signed Distance Fields
The signed distance field of a surface can effectively support many geometry processing tasks such as decimation, smoothing, and Boolean operations since it provides efficient a...
Jianhua Wu, Leif Kobbelt
100
Voted
CVPR
2008
IEEE
16 years 2 months ago
Approximate earth mover's distance in linear time
The earth mover's distance (EMD) [16] is an important perceptually meaningful metric for comparing histograms, but it suffers from high (O(N3 log N)) computational complexity...
Sameer Shirdhonkar, David W. Jacobs
SIAMCOMP
2000
88views more  SIAMCOMP 2000»
15 years 7 days ago
Gadgets, Approximation, and Linear Programming
We present a linear programming-based method for nding \gadgets", i.e., combinatorial structures reducing constraints of one optimization problem to constraints of another. A...
Luca Trevisan, Gregory B. Sorkin, Madhu Sudan, Dav...
101
Voted
AIPS
2004
15 years 1 months ago
Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Branislav Kveton, Milos Hauskrecht