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» Bias and Variance Approximation in Value Function Estimates
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ESANN
2003
13 years 8 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...
ICCSA
2010
Springer
14 years 2 months ago
String Matching with Mismatches by Real-Valued FFT
String matching with mismatches is a basic concept of information retrieval with some kinds of approximation. This paper proposes an FFT-based algorithm for the problem of string ...
Kensuke Baba
CSDA
2008
67views more  CSDA 2008»
13 years 7 months ago
How useful are approximations to mean and variance of the index of dissimilarity?
Sociologists, demographers, and economists often use the index of dissimilarity, D, to describe the extent of racial, ethnic, spatial, or areal dissimilarity (or segregation) of d...
Madhuri S. Mulekar, John C. Knutson, Jyoti A. Cham...
BMCBI
2007
107views more  BMCBI 2007»
13 years 7 months ago
A general and efficient method for estimating continuous IBD functions for use in genome scans for QTL
Background: Identity by descent (IBD) matrix estimation is a central component in mapping of Quantitative Trait Loci (QTL) using variance component models. A large number of algor...
Francois Besnier, Örjan Carlborg
ICML
2001
IEEE
14 years 8 months ago
Off-Policy Temporal Difference Learning with Function Approximation
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
Doina Precup, Richard S. Sutton, Sanjoy Dasgupta