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» On Unbiased Linear Approximations
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94
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NIPS
2001
15 years 2 months ago
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
Gregory Z. Grudic, Lyle H. Ungar
64
Voted
MOC
1998
95views more  MOC 1998»
15 years 8 days ago
The Trotter-Kato theorem and approximation of PDEs
Abstract. We present formulations of the Trotter-Kato theorem for approximation of linear C0-semigroups which provide very useful framework when convergence of numerical approximat...
Kazufumi Ito, Franz Kappel
JAIR
2006
122views more  JAIR 2006»
15 years 17 days ago
Solving Factored MDPs with Hybrid State and Action Variables
Efficient representations and solutions for large decision problems with continuous and discrete variables are among the most important challenges faced by the designers of automa...
Branislav Kveton, Milos Hauskrecht, Carlos Guestri...
CAGD
1999
101views more  CAGD 1999»
15 years 8 days ago
Approximation algorithms for developable surfaces
By its dual representation, a developable surface can be viewed as a curve of dual projective 3-space. After introducing an appropriate metric in the dual space and restricting ou...
Helmut Pottmann, Johannes Wallner
STOC
2007
ACM
146views Algorithms» more  STOC 2007»
16 years 27 days ago
Playing games with approximation algorithms
In an online linear optimization problem, on each period t, an online algorithm chooses st S from a fixed (possibly infinite) set S of feasible decisions. Nature (who may be adve...
Sham M. Kakade, Adam Tauman Kalai, Katrina Ligett