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NIPS
2003
15 years 5 months ago
On the Dynamics of Boosting
In order to understand AdaBoost’s dynamics, especially its ability to maximize margins, we derive an associated simplified nonlinear iterated map and analyze its behavior in lo...
Cynthia Rudin, Ingrid Daubechies, Robert E. Schapi...
WWW
2001
ACM
16 years 4 months ago
An intelligent distributed environment for active learning
Active learning is an e ective learning approach. In this paper, we present an intelligent agent assisted environment for active learning. The system is to better support studentc...
Yi Shang, Hongchi Shi, Su-Shing Chen
SDM
2009
SIAM
191views Data Mining» more  SDM 2009»
16 years 1 months ago
Adaptive Concept Drift Detection.
An established method to detect concept drift in data streams is to perform statistical hypothesis testing on the multivariate data in the stream. Statistical decision theory off...
Anton Dries, Ulrich Rückert
152
Voted
ML
2002
ACM
167views Machine Learning» more  ML 2002»
15 years 3 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...
130
Voted
GECCO
2006
Springer
151views Optimization» more  GECCO 2006»
15 years 7 months ago
Sporadic model building for efficiency enhancement of hierarchical BOA
This paper describes and analyzes sporadic model building, which can be used to enhance the efficiency of the hierarchical Bayesian optimization algorithm (hBOA) and other advance...
Martin Pelikan, Kumara Sastry, David E. Goldberg