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CORR
2011
Springer
127views Education» more  CORR 2011»
13 years 11 days ago
Generalized Boosting Algorithms for Convex Optimization
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
Alexander Grubb, J. Andrew Bagnell
ICPR
2008
IEEE
14 years 9 months ago
Training sequential on-line boosting classifier for visual tracking
On-line boosting allows to adapt a trained classifier to changing environmental conditions or to use sequentially available training data. Yet, two important problems in the on-li...
Helmut Grabner, Horst Bischof, Jan Sochman, Jiri M...
EMNLP
2004
13 years 10 months ago
Trained Named Entity Recognition using Distributional Clusters
This work applies boosted wrapper induction (BWI), a machine learning algorithm for information extraction from semi-structured documents, to the problem of named entity recogniti...
Dayne Freitag
EUROGP
2007
Springer
161views Optimization» more  EUROGP 2007»
14 years 2 months ago
Mining Distributed Evolving Data Streams Using Fractal GP Ensembles
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
COLT
2001
Springer
14 years 1 months ago
Agnostic Boosting
We prove strong noise-tolerance properties of a potential-based boosting algorithm, similar to MadaBoost (Domingo and Watanabe, 2000) and SmoothBoost (Servedio, 2003). Our analysi...
Shai Ben-David, Philip M. Long, Yishay Mansour