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IWANN
1999
Springer
15 years 10 months ago
Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
R. Matthew Kretchmar, Charles W. Anderson
COCO
1994
Springer
140views Algorithms» more  COCO 1994»
15 years 10 months ago
Random Debaters and the Hardness of Approximating Stochastic Functions
A probabilistically checkable debate system (PCDS) for a language L consists of a probabilisticpolynomial-time veri er V and a debate between Player 1, who claims that the input x ...
Anne Condon, Joan Feigenbaum, Carsten Lund, Peter ...
ICDCS
2010
IEEE
15 years 10 months ago
Existence Theorems and Approximation Algorithms for Generalized Network Security Games
—Aspnes et al [2] introduced an innovative game for modeling the containment of the spread of viruses and worms (security breaches) in a network. In this model, nodes choose to i...
V. S. Anil Kumar, Rajmohan Rajaraman, Zhifeng Sun,...
ESANN
2003
15 years 7 months ago
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Fo...
CAD
2006
Springer
15 years 6 months ago
An efficient, error-bounded approximation algorithm for simulating quasi-statics of complex linkages
Design and analysis of articulated mechanical structures, commonly referred to as linkages, is an integral part of any CAD/CAM system. The most common approaches formulate the pro...
Stephane Redon, Ming C. Lin