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ICCCN
2007
IEEE
15 years 6 months ago
Online Selection of Tracking Features using AdaBoost
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
Ying-Jia Yeh, Chiou-Ting Hsu
169
Voted
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 6 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
JMLR
2010
154views more  JMLR 2010»
15 years 1 months ago
MOA: Massive Online Analysis
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collecti...
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernha...
140
Voted
CLUSTER
2006
IEEE
15 years 6 months ago
Exploiting redundancy to boost performance in a RAID-10 style cluster-based file system
Yifeng Zhu, Hong Jiang, Xiao Qin, Dan Feng, David ...