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» Practical Bias Variance Decomposition
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ICASSP
2011
IEEE
12 years 11 months ago
Performance analysis of MDL criterion for the detection of noncircular or/and nonGaussian components
This paper presents an asymptotic analysis of the eigen value decomposition (EVD) of the sample covariance matrix associated with independent identically distributed (IID) non nec...
Jean Pierre Delmas, Yann Meurisse
ICASSP
2011
IEEE
12 years 11 months ago
Evolutive method based on a generalized eigenvalue decomposition to estimate time varying autoregressive parameters from noisy o
A great deal of interest has been paid to the estimation of time-varying autoregressive (TVAR) parameters. However, when the observations are disturbed by an additive white measur...
Hiroshi Ijima, Julien Petitjean, Eric Grivel
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...
ICML
1997
IEEE
14 years 8 months ago
Characterizing the generalization performance of model selection strategies
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
Dale Schuurmans, Lyle H. Ungar, Dean P. Foster
UAI
2001
13 years 8 months ago
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
Lex Weaver, Nigel Tao