Active Bibliography

515 An Efficient Boosting Algorithm for Combining Preferences – Raj Dharmarajan Iyer , Jr. - 1999
69 Extracting Comprehensible Models from Trained Neural Networks – W. Craven - 1996
50 Theoretical Views of Boosting and Applications – Robert E. Schapire - 1999
564 A Short Introduction to Boosting – Yoav Freund, Robert E. Schapire - 1999
26 Prototype Selection for Composite Nearest Neighbor Classifiers – David B. Skalak - 1997
90 Using Output Codes to Boost Multiclass Learning Problems – Robert E. Schapire - 1997
38 Boosting and hard-core sets – Adam R. Klivans, Rocco A. Servedio - 1999
2307 A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting – Yoav Freund, Robert E. Schapire - 1997
539 An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants – Eric Bauer, Ron Kohavi - 1999
12 Discussion of the Paper ‘Arcing Classifiers’ by Leo Breiman – Yoav Freund, Robert E. Schapire - 1998
721 Boosting the margin: A new explanation for the effectiveness of voting methods – Robert E. Schapire, Peter Bartlett, Yoav Freund, Wee Sun Lee - 1997
38 Simplifying Decision Trees: A Survey – Leonard A. Breslow, David W. Aha - 1996
3 Minimum Majority Classification and Boosting – Philip M. Long - 2002
Contents 1 Ensemble methods: a review 3 – Matteo Re, Giorgio Valentini
22 The Sources of Increased Accuracy for Two Proposed Boosting Algorithms – David B. Skalak - 1996
16 Robust Combining of Disparate Classifiers through Order Statistics – Kagan Tumer, Joydeep Ghosh - 2001
110 An introduction to boosting and leveraging – Ron Meir, Gunnar Rätsch - 2003
LETTER Communicated by Robert Jacobs Boosted Mixture of Experts: An Ensemble Learning Scheme – Ran Avnimelech, Nathan Intrator
27 Boosted Mixture of Experts: An ensemble learning scheme – Ran Avnimelech, Nathan Intrator - 1999