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ICML
2007
IEEE
14 years 8 months ago
Tracking value function dynamics to improve reinforcement learning with piecewise linear function approximation
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
Chee Wee Phua, Robert Fitch
MFCS
2009
Springer
13 years 12 months ago
An Improved Approximation Bound for Spanning Star Forest and Color Saving
We present a simple algorithm for the maximum spanning star forest problem. We take advantage of the fact that the problem is a special case of complementary set cover and we adapt...
Stavros Athanassopoulos, Ioannis Caragiannis, Chri...
CVIU
2008
132views more  CVIU 2008»
13 years 7 months ago
Global parametric image alignment via high-order approximation
The estimation of parametric global motion is one of the cornerstones of computer vision. Such schemes are able to estimate various motion models (translation, rotation, affine, p...
Yosi Keller, Amir Averbuch
ORL
2007
47views more  ORL 2007»
13 years 6 months ago
A simpler and better derandomization of an approximation algorithm for single source rent-or-buy
We present a very simple way of derandomizing the algorithm proposed by Gupta, Kumar and Roughgarden for Single Source Rent-or-Buy by using the method of conditional expectation. ...
David P. Williamson, Anke van Zuylen
SODA
2003
ACM
158views Algorithms» more  SODA 2003»
13 years 8 months ago
Faster approximation algorithms for the minimum latency problem
We give a 7.18-approximation algorithm for the minimum latency problem that uses only O(n log n) calls to the prize-collecting Steiner tree (PCST) subroutine of Goemans and Willia...
Aaron Archer, David P. Williamson