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ICML
2004
IEEE
14 years 9 months 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
CIKM
2009
Springer
14 years 3 months ago
A general magnitude-preserving boosting algorithm for search ranking
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang...
ICIP
2008
IEEE
14 years 3 months ago
Boosted Interactively Distributed Particle Filter for automatic multi-object tracking
In this paper, we propose a Boosted Interactively Distributed Particle Filter (BIDPF) to address the problem of automatic multi-object tracking in the application of player tracki...
Yi Wu, Xiaofeng Tong, Yimin Zhang, Hanqing Lu
ICIP
2009
IEEE
14 years 9 months ago
Early Terminating Algorithms For Adaboost Based Detectors
In this paper we propose an early termination algorithm for speeding up the detection phase of the Adaboost based detectors. In the basic algorithm, at a specific search location,...
ICDCS
2005
IEEE
14 years 2 months ago
The Impossibility of Boosting Distributed Service Resilience
We prove two theorems saying that no distributed system in which processes coordinate using reliable registers and -resilient services can solve the consensus problem in the prese...
Paul C. Attie, Rachid Guerraoui, Petr Kouznetsov, ...