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CVPR
2010
IEEE
13 years 7 months ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
CORR
2002
Springer
63views Education» more  CORR 2002»
13 years 7 months ago
Robust Classification with Context-Sensitive Features
This paper addresses the problem of classifying observations when features are context-sensitive, especially when the testing set involves a context that is different from the tra...
Peter D. Turney
INFOCOM
2007
IEEE
14 years 1 months ago
Exploiting Hidden Convexity For Flexible And Robust Resource Allocation In Cellular Networks
— A systematic approach to solve seemingly nonconvex resource allocation problems in wireless cellular networks is studied in this paper. By revealing and exploiting the hidden c...
Chee-Wei Tan, Daniel Pérez Palomar, Mung Ch...
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
13 years 8 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb
GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
13 years 11 months ago
Robustness in cooperative coevolution
Though recent analysis of traditional cooperative coevolutionary algorithms (CCEAs) casts doubt on their suitability for static optimization tasks, our experience is that the algo...
R. Paul Wiegand, Mitchell A. Potter