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» How to process uncertainty in machine learning
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DATAMINE
2010
122views more  DATAMINE 2010»
13 years 7 months ago
Three naive Bayes approaches for discrimination-free classification
In this paper, we investigate how to modify the Naive Bayes classifier in order to perform classification that is restricted to be independent with respect to a given sensitive att...
Toon Calders, Sicco Verwer
CCE
2006
13 years 7 months ago
New approaches for representing, analyzing and visualizing complex kinetic transformations
Complex kinetic mechanisms involving thousands of reacting species and tens of thousands of reactions are currently required for the rational analysis of modern combustion systems...
Ioannis P. Androulakis
CVPR
2008
IEEE
14 years 1 months ago
General Constraints for Batch Multiple-Target Tracking Applied to Large-Scale Videomicroscopy
While there is a large class of Multiple-Target Tracking (MTT) problems for which batch processing is possible and desirable, batch MTT remains relatively unexplored in comparis...
Kevin Smith, Alan Carleton, Vincent Lepetit
FTML
2008
185views more  FTML 2008»
13 years 7 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan
AIHC
2007
Springer
14 years 1 months ago
Affect Detection and an Automated Improvisational AI Actor in E-Drama
Enabling machines to understand emotions and feelings of the human users in their natural language textual input during interaction is a challenging issue in Human Computing. Our w...
Li Zhang, Marco Gillies, John A. Barnden, Robert J...