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» Learning Classifiers from Semantically Heterogeneous Data
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CVPR
2005
IEEE
15 years 8 days ago
Learning Spatiotemporal T-Junctions for Occlusion Detection
The goal of motion segmentation and layer extraction can be viewed as the detection and localization of occluding surfaces. A feature that has been shown to be a particularly stro...
Nicholas Apostoloff, Andrew W. Fitzgibbon
JMLR
2010
117views more  JMLR 2010»
13 years 5 months ago
Bayesian Online Learning for Multi-label and Multi-variate Performance Measures
Many real world applications employ multivariate performance measures and each example can belong to multiple classes. The currently most popular approaches train an SVM for each ...
Xinhua Zhang, Thore Graepel, Ralf Herbrich
IJISTA
2007
124views more  IJISTA 2007»
13 years 10 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
DNA
2005
Springer
118views Bioinformatics» more  DNA 2005»
14 years 3 months ago
Molecular Learning of wDNF Formulae
We introduce a class of generalized DNF formulae called wDNF or weighted disjunctive normal form, and present a molecular algorithm that learns a wDNF formula from training example...
Byoung-Tak Zhang, Ha-Young Jang
DAGSTUHL
2007
13 years 11 months ago
Parallel universes to improve the diagnosis of cardiac arrhythmias
arrhythmias (extended abstract) Elisa Fromont, Ren´e Quiniou, Marie-Odile Cordier We are interested in using parallel universes to learn interpretable models that can be subseque...
Élisa Fromont, Rene Quiniou, Marie-Odile Co...