Active Bibliography

111 An introduction to boosting and leveraging – Ron Meir, Gunnar Rätsch - 2003
50 Theoretical Views of Boosting and Applications – Robert E. Schapire - 1999
571 A Short Introduction to Boosting – Yoav Freund, Robert E. Schapire - 1999
2 Faithful Representations and Moments of Satisfaction: Probabilistic Methods in Learning and Logic – Lidror Troyansky, Prof Naftali Tishby - 1998
Introduction to Boosting: Origin, Practice and Recent Developments – Naoki Abe
6 A note on margin-based loss functions – Yi Lin - 2004
Learning via Internal Representation (Extended Abstract) – Eli Dichterman - 1998
8 A Real generalization of discrete AdaBoost – Richard Nock , Frank Nielsen - 2007
1 Learning with Kernel Machine Architectures – Theodoros Evgeniou, Tomaso Poggio, Helen Whitaker, Professor Brain, Cognitive Sciences, Arthur C. Smith - 2000
15 Boosting Methods for Regression – Nigel Duffy, David Helmbold - 200
721 Boosting the margin: A new explanation for the effectiveness of voting methods – Robert E. Schapire, Peter Bartlett, Yoav Freund, Wee Sun Lee - 1997
66 On the Bayes-risk consistency of regularized boosting methods – Gábor Lugosi, Nicolas Vayatis
39 Online ensemble learning – Nikunj Chandrakant Oza - 2001
26 Prototype Selection for Composite Nearest Neighbor Classifiers – David B. Skalak - 1997
5 Performance and efficiency: Recent advances in supervised learning – Sheng Ma, Chuanyi Ji - 1999
On the Existence of Linear Weak Learners and Applications to Boosting – Shie Mannor, Ron Meir, Yoshua Bengio, Dale Schuurmans - 2002
38 Boosting algorithms: Regularization, prediction and model fitting – Peter Bühlmann, Torsten Hothorn - 2007
42 Constructing Boosting Algorithms from SVMs: An Application to One-class Classification – Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Klaus-Robert Müller - 2002
8 On weak base hypotheses and their implications for boosting regression and classification – Wenxin Jiang - 1999