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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
CIARP
2004
Springer
13 years 11 months ago
New Bounds and Approximations for the Error of Linear Classifiers
In this paper, we derive lower and upper bounds for the probability of error for a linear classifier, where the random vectors representing the underlying classes obey the multivar...
Luís G. Rueda
STOC
2009
ACM
172views Algorithms» more  STOC 2009»
14 years 8 months ago
Linear time approximation schemes for the Gale-Berlekamp game and related minimization problems
We design a linear time approximation scheme for the GaleBerlekamp Switching Game and generalize it to a wider class of dense fragile minimization problems including the Nearest C...
Marek Karpinski, Warren Schudy
IPL
2008
95views more  IPL 2008»
13 years 7 months ago
Approximating maximum satisfiable subsystems of linear equations of bounded width
We consider the problem known as MAX-SATISFY: given a system of m linear equations over the rationals, find a maximum set of equations that can be satisfied. Let r be the width of...
Zeev Nutov, Daniel Reichman
AUTOMATICA
2007
179views more  AUTOMATICA 2007»
13 years 7 months ago
Approximate bisimulation relations for constrained linear systems
In this paper, we define the notion of approximate bisimulation relation between two continuous systems. While exact bisimulation requires that the observations of two systems ar...
Antoine Girard, George J. Pappas