Online Bagging and Boosting (2001)

by Nikunj C. Oza , Stuart Russell
Venue:In Artificial Intelligence and Statistics 2001
Citations:82 - 1 self

Documents Related by Co-Citation

137 Online Boosting and Vision – Helmut Grabner, Horst Bischof - 2006
2329 A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting – Yoav Freund, Robert E. Schapire - 1996
2071 Rapid object detection using a boosted cascade of simple features – Paul Viola, Michael Jones - 2001
115 A streaming ensemble algorithm (SEA) for large-scale classification – W. Nick Street - 2001
43 Online detection and classification of moving objects using progressively improving detectors – Omar Javed - 2005
292 Mining high-speed data streams – Pedro Domingos - 2000
192 Ensemble Tracking – Shai Avidan - 2007
252 Mining time-changing data streams – Geoff Hulten, Laurie Spencer, Pedro Domingos - 2001
25 Online Ensemble Learning: An Empirical Study – Alan Fern, Robert Givan - 2000
1225 Additive Logistic Regression: a Statistical View of Boosting – Jerome Friedman, Trevor Hastie, Robert Tibshirani - 1998
320 The Boosting Approach to Machine Learning: An Overview – Robert E. Schapire - 2002
93 Unsupervised Improvement of Visual Detectors using Co-Training – Anat Levin - 2003
37 Experimental Comparisons of Online and Batch Versions of Bagging and Boosting – Nikunj C. Oza, Stuart Russell
92 Robust Fragments-based Tracking using the Integral Histogram – Amit Adam, Ehud Rivlin, Ilan Shimshoni - 2006
223 On-line selection of discriminative tracking features – Robert T. Collins, Yanxi Liu, Marius Leordeanu - 2003
9023 The Nature of Statistical Learning Theory – Vladimir N. Vapnik - 1995
1639 Experiments with a New Boosting Algorithm – Yoav Freund, Robert E. Schapire - 1996
2509 Bagging Predictors – Leo Breiman, Leo Breiman - 1996
87 Learning Object Detection from a Small Number of Examples: the Importance of Good Features – kobi Levi, Yair Weiss, Of Good Features - 2004