|
16
|
The State of Boosting
– Greg Ridgeway
- 1999
|
|
78
|
An introduction to boosting and leveraging
– Ron Meir, Gunnar Rätsch
- 2003
|
|
26
|
Online ensemble learning
– Nikunj Chandrakant Oza
- 2001
|
|
2
|
Upper bounds for error rates associated to linear combination of classifiers
– Alejandro Murua
- 1999
|
|
383
|
An Efficient Boosting Algorithm for Combining Preferences
– Raj Dharmarajan Iyer , Jr.
- 1999
|
|
10
|
Boosting Methods for Regression
– Nigel Duffy, David Helmbold
- 200
|
|
82
|
Boosting with the L_2-Loss: Regression and Classification
– Peter Bühlmann, Bin Yu
- 2001
|
|
13
|
AdaBoost is consistent
– Peter L. Bartlett, Yoav Freund
- 2006
|
|
7
|
Experiments with AdaBoost.RT, an Improved Boosting Scheme for Regression
– D. L. Shrestha, D. P. Solomatine
|
|
435
|
A Short Introduction to Boosting
– Yoav Freund, Robert E. Schapire
- 1999
|
|
47
|
On the Bayes-risk consistency of regularized boosting methods
– Gábor Lugosi, Nicolas Vayatis
|
|
78
|
Using Output Codes to Boost Multiclass Learning Problems
– Robert E. Schapire
- 1997
|
|
449
|
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
– Eric Bauer, Ron Kohavi
- 1999
|
|
606
|
Boosting the margin: A new explanation for the effectiveness of voting methods
– Robert E. Schapire, Peter Bartlett, Yoav Freund, Wee Sun Lee
- 1997
|
|
1
|
Integrating Boosting and Stochastic Attribute Selection Committees for Further Improving the Performance of Decision Tree Learning
– Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
- 1998
|
|
23
|
Piecewise-polynomial regression trees
– Probal Chaudhuri, Min-ching Huang, Wei-yin Loh, Ruji Yao
- 1994
|
|
40
|
A Statistical Perspective on Knowledge Discovery in Databases
– John F. Elder, IV, Daryl Pregibon
- 1996
|
|
|
On the Existence of Linear Weak Learners and Applications to Boosting
– Shie Mannor, Ron Meir, Yoshua Bengio, Dale Schuurmans
- 2002
|
|
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A modification of AdaBoost: A preliminary report
– Carlos Domingo, Osamu Watanabe
- 1999
|
