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» Empirical Bernstein Boosting
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COLT
2004
Springer
14 years 3 months ago
Boosting Based on a Smooth Margin
Abstract. We study two boosting algorithms, Coordinate Ascent Boosting and Approximate Coordinate Ascent Boosting, which are explicitly designed to produce maximum margins. To deri...
Cynthia Rudin, Robert E. Schapire, Ingrid Daubechi...
ICML
2008
IEEE
14 years 10 months ago
An empirical evaluation of supervised learning in high dimensions
In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
Rich Caruana, Nikolaos Karampatziakis, Ainur Yesse...
TIT
2010
88views Education» more  TIT 2010»
13 years 4 months ago
Zero-rate feedback can achieve the empirical capacity
The utility of limited feedback for coding over an individual sequence of DMCs is investigated. This study complements recent results showing how limited or noisy feedback can boos...
Krishnan Eswaran, Anand D. Sarwate, Anant Sahai, M...
EVOW
2010
Springer
14 years 4 months ago
Adaptive Noisy Optimization
In this paper, adaptive noisy optimization on variants of the noisy sphere model is considered, i.e. optimization in which the same algorithm is able to adapt to several frameworks...
Philippe Rolet, Olivier Teytaud
ICIP
2009
IEEE
14 years 11 months ago
Object Detection Via Boosted Deformable Features
It is a common practice to model an object for detection tasks as a boosted ensemble of many models built on features of the object. In this context, features are defined as subre...