A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting (1997)

by Yoav Freund , Robert E. Schapire
Citations:2304 - 59 self

Active Bibliography

and – Yoav Freund, Robert E. Schapire - 1996
515 An Efficient Boosting Algorithm for Combining Preferences – Raj Dharmarajan Iyer , Jr. - 1999
564 A Short Introduction to Boosting – Yoav Freund, Robert E. Schapire - 1999
50 Theoretical Views of Boosting and Applications – Robert E. Schapire - 1999
134 SCHAPIRE: Adaptive game playing using multiplicative weights – Yoav Freund, Robert E. Schapire - 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
63 Competitive on-line statistics – Volodya Vovk - 1999
61 On-line algorithms in machine learning – Avrim Blum - 1998
136 Universal prediction – Neri Merhav, Senior Member, Meir Feder, Senior Member - 1998
3 Minimum Majority Classification and Boosting – Philip M. Long - 2002
35 Combinations of Weak Classifiers – Chuanyi Ji, et al. - 1997
39 Online ensemble learning – Nikunj Chandrakant Oza - 2001
5 Performance and efficiency: Recent advances in supervised learning – Sheng Ma, Chuanyi Ji - 1999
13 Universal switching linear least squares prediction – Suleyman S. Kozat, Andrew C. Singer - 2006
Theory and Applications of Predictors That Specialize – Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
93 Using and combining predictors that specialize – Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth - 1997
115 Regret in the On-line Decision Problem – Dean P. Foster, Rakesh Vohra - 1999
6 Adaptive Routing Using Expert Advice – András György, György Ottucsák - 2006
75 Sequential Prediction of Individual Sequences Under General Loss Functions – David Haussler, Jyrki Kivinen, Manfred K. Warmuth - 1998