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104
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SDM
2007
SIAM
104views Data Mining» more  SDM 2007»
15 years 4 months ago
Boosting Optimal Logical Patterns Using Noisy Data
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
Noam Goldberg, Chung-chieh Shan
141
Voted
PAKDD
2009
ACM
171views Data Mining» more  PAKDD 2009»
15 years 7 months ago
Detecting Abnormal Events via Hierarchical Dirichlet Processes
Abstract. Detecting abnormal event from video sequences is an important problem in computer vision and pattern recognition and a large number of algorithms have been devised to tac...
Xian-Xing Zhang, Hua Liu, Yang Gao, Derek Hao Hu
131
Voted
ICDM
2009
IEEE
160views Data Mining» more  ICDM 2009»
15 years 9 months ago
Fast Online Training of Ramp Loss Support Vector Machines
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Zhuang Wang, Slobodan Vucetic
90
Voted
AIED
2009
Springer
15 years 9 months ago
Revisiting Ill-Definedness and the Consequences for ITSs
: ITSs for ill-defined domains have attracted a lot of attention recently, which is well-deserved, as such ITSs are hard to develop. The first step towards such ITSs is reaching a ...
Antonija Mitrovic, Amali Weerasinghe
116
Voted
ECML
2007
Springer
15 years 8 months ago
Scale-Space Based Weak Regressors for Boosting
Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based...
Jin Hyeong Park, Chandan K. Reddy