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CSDA
2004
124views more  CSDA 2004»
15 years 6 months ago
Fast and robust discriminant analysis
The goal of discriminant analysis is to obtain rules that describe the separation between groups of observations. Moreover it allows to classify new observations into one of the k...
Mia Hubert, Katrien van Driessen
AUTOMATICA
2005
112views more  AUTOMATICA 2005»
15 years 6 months ago
Robust maximum-likelihood estimation of multivariable dynamic systems
This paper examines the problem of estimating linear time-invariant state-space system models. In particular it addresses the parametrization and numerical robustness concerns tha...
Stuart Gibson, Brett Ninness
CORR
2000
Springer
84views Education» more  CORR 2000»
15 years 6 months ago
Robust Classification for Imprecise Environments
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building ro...
Foster J. Provost, Tom Fawcett
CSDA
2007
152views more  CSDA 2007»
15 years 6 months ago
Robust variable selection using least angle regression and elemental set sampling
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Lauren McCann, Roy E. Welsch
PRL
2010
310views more  PRL 2010»
15 years 5 months ago
A Lagrangian Half-Quadratic approach to robust estimation and its applications to road scene analysis
We consider the problem of fitting linearly parameterized models, that arises in many computer vision problems such as road scene analysis. Data extracted from images usually cont...
Jean-Philippe Tarel, Pierre Charbonnier