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COLT
2001
Springer
13 years 10 months ago
Agnostic Boosting
We prove strong noise-tolerance properties of a potential-based boosting algorithm, similar to MadaBoost (Domingo and Watanabe, 2000) and SmoothBoost (Servedio, 2003). Our analysi...
Shai Ben-David, Philip M. Long, Yishay Mansour
COLT
2000
Springer
13 years 10 months ago
PAC Analogues of Perceptron and Winnow via Boosting the Margin
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Rocco A. Servedio
COLT
2000
Springer
13 years 10 months ago
Model Selection and Error Estimation
We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalizatio...
Peter L. Bartlett, Stéphane Boucheron, G&aa...
COLT
2000
Springer
13 years 10 months ago
On the Learnability and Design of Output Codes for Multiclass Problems
Output coding is a general framework for solving multiclass categorization problems. Previous research on output codes has focused on building multiclass machines given predefine...
Koby Crammer, Yoram Singer
COLT
2000
Springer
13 years 9 months ago
The Role of Critical Sets in Vapnik-Chervonenkis Theory
In the present paper, we present the theoretical basis, as well as an empirical validation, of a protocol designed to obtain effective VC dimension estimations in the case of a si...
Nicolas Vayatis