|
1714
|
A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting
– Yoav Freund, Robert E. Schapire
- 1997
|
|
383
|
An Efficient Boosting Algorithm for Combining Preferences
– Raj Dharmarajan Iyer , Jr.
- 1999
|
|
435
|
A Short Introduction to Boosting
– Yoav Freund, Robert E. Schapire
- 1999
|
|
39
|
Theoretical Views of Boosting and Applications
– Robert E. Schapire
- 1999
|
|
267
|
How to Use Expert Advice
– Nicolò Cesa-Bianchi, Yoav Freund, David Haussler, David P. Helmbold, Robert E. Schapire, Manfred K. Warmuth
- 1997
|
|
98
|
Regret in the On-line Decision Problem
– Dean P. Foster, Rakesh Vohra
- 1999
|
|
39
|
Competitive on-line statistics
– Volodya Vovk
- 1999
|
|
99
|
Universal Prediction
– Neri Merhav, Meir Feder
- 1998
|
|
46
|
On-line algorithms in machine learning
– Avrim Blum
- 1998
|
|
106
|
Adaptive Game Playing Using Multiplicative Weights
– Yoav Freund, Robert E. Schapire
|
|
65
|
Extracting Comprehensible Models from Trained Neural Networks
– W. Craven
- 1996
|
|
606
|
Boosting the margin: A new explanation for the effectiveness of voting methods
– Robert E. Schapire, Peter Bartlett, Yoav Freund, Wee Sun Lee
- 1997
|
|
26
|
Online ensemble learning
– Nikunj Chandrakant Oza
- 2001
|
|
35
|
Predicting a Binary Sequence Almost as Well as the Optimal Biased Coin
– Yoav Freund
- 1996
|
|
58
|
Sequential Prediction of Individual Sequences Under General Loss Functions
– David Haussler, Jyrki Kivinen, Manfred K. Warmuth
- 1998
|
|
|
Theory and Applications of Predictors That Specialize
– Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
|
|
76
|
Using and Combining Predictors That Specialize
– Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
- 1997
|
|
|
Lectures on Prediction of Individual Sequences
– Gábor Lugosi
- 2001
|
|
|
Reinforcement Learning Without Rewards
– Umar Ali Syed
- 2010
|
