In this paper, we present a robust feature extraction framework based on informationtheoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's...
A performance and robustness study for on-line signature veri cation is presented. Experiments are carried out on the MCYT database comprising 16,500 signatures from 330 subjects,...
This is an overview of the robust resource allocation research efforts that have been and continue to be conducted by the CSU Robustness in Computer Systems Group. Parallel and di...
David L. Janovy, Jay Smith, Howard Jay Siegel, Ant...
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
In this paper we present a non parametric density-based data reduction technique designed to be used in robust parameter estimation problems. Existing approaches are focused on red...