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ICML
2004
IEEE
16 years 11 days ago
Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
3DIM
2003
IEEE
15 years 4 months ago
Reliable and Rapidly-Converging ICP Algorithm Using Multiresolution Smoothing
Autonomous range acquisition for 3D modeling requires reliable range registration, for both the precise localization of the sensor and combining the data from multiple scans for v...
Kok-Lim Low, Anselmo Lastra
COLT
2008
Springer
15 years 1 months ago
On the Margin Explanation of Boosting Algorithms
Much attention has been paid to the theoretical explanation of the empirical success of AdaBoost. The most influential work is the margin theory, which is essentially an upper bou...
Liwei Wang, Masashi Sugiyama, Cheng Yang, Zhi-Hua ...
ECML
2007
Springer
15 years 5 months ago
Avoiding Boosting Overfitting by Removing Confusing Samples
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
Alexander Vezhnevets, Olga Barinova
COLT
2005
Springer
15 years 5 months ago
Margin-Based Ranking Meets Boosting in the Middle
Abstract. We present several results related to ranking. We give a general margin-based bound for ranking based on the L∞ covering number of the hypothesis space. Our bound sugge...
Cynthia Rudin, Corinna Cortes, Mehryar Mohri, Robe...