Active Bibliography

110 An introduction to boosting and leveraging – Ron Meir, Gunnar Rätsch - 2003
50 Theoretical Views of Boosting and Applications – Robert E. Schapire - 1999
515 An Efficient Boosting Algorithm for Combining Preferences – Raj Dharmarajan Iyer , Jr. - 1999
721 Boosting the margin: A new explanation for the effectiveness of voting methods – Robert E. Schapire, Peter Bartlett, Yoav Freund, Wee Sun Lee - 1997
19 Barrier Boosting – Gunnar Rätsch, Manfred Warmuth, Sebastian Mika, Takashi Onoda, Steven Lemm, Klaus-Robert Müller
c ○ 2002 Kluwer Academic Publishers. Manufactured in The Netherlands. Boosting Methods for Regression ∗ – Nigel Duffy, David Helmbold, Jyrki Kivinen
15 Boosting Methods for Regression – Nigel Duffy, David Helmbold - 200
9 An Empirical Comparison of Three Boosting Algorithms on Real Data Sets with Artificial Class Noise – Ross A. McDonald, David J. Hand, Idris A. Eckley - 2003
41 Constructing Boosting Algorithms from SVMs: An Application to One-class Classification – Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Klaus-Robert Müller - 2002
8 A Real generalization of discrete AdaBoost – Richard Nock , Frank Nielsen - 2007
26 The State of Boosting – Greg Ridgeway - 1999
39 Online ensemble learning – Nikunj Chandrakant Oza - 2001
3 Minimum Majority Classification and Boosting – Philip M. Long - 2002
6 A note on margin-based loss functions – Yi Lin - 2004
2 A robust boosting algorithm – Richard Nock, Patrice Lefaucheur - 2002
22 AdaBoost is consistent – Peter L. Bartlett, Yoav Freund - 2006
3 A Fourier analysis based approach to learning decision trees in a distributed environment – Byung-hoon Park, Rajeev Ayyagari - 2001
2 Creating Diverse Ensemble Classifiers – Prem Melville, Supervisor Raymond, J. Mooney - 2003
115 Boosting Algorithms as Gradient Descent – Llew Mason, Jonathan Baxter, Peter Bartlett, Marcus Frean - 2000