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185
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COLT
2000
Springer
15 years 11 months ago
Entropy Numbers of Linear Function Classes
This paper collects together a miscellany of results originally motivated by the analysis of the generalization performance of the “maximum-margin” algorithm due to Vapnik and...
Robert C. Williamson, Alex J. Smola, Bernhard Sch&...
184
Voted
COLT
1999
Springer
15 years 11 months ago
Boosting as Entropy Projection
We consider the AdaBoost procedure for boosting weak learners. In AdaBoost, a key step is choosing a new distribution on the training examples based on the old distribution and th...
Jyrki Kivinen, Manfred K. Warmuth
257
Voted
EUROCOLT
1999
Springer
15 years 11 months ago
Averaging Expert Predictions
We consider algorithms for combining advice from a set of experts. In each trial, the algorithm receives the predictions of the experts and produces its own prediction. A loss func...
Jyrki Kivinen, Manfred K. Warmuth
176
Voted
ILP
1999
Springer
15 years 11 months ago
Rule Evaluation Measures: A Unifying View
Numerous measures are used for performance evaluation in machine learning. In predictive knowledge discovery, the most frequently used measure is classification accuracy. With new...
Nada Lavrac, Peter A. Flach, Blaz Zupan
184
Voted
COLT
1998
Springer
15 years 11 months ago
Improved Boosting Algorithms using Confidence-Rated Predictions
Abstract. We describe several improvements to Freund and Schapire's AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each o...
Robert E. Schapire, Yoram Singer