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117
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ICML
2005
IEEE
16 years 1 months ago
A smoothed boosting algorithm using probabilistic output codes
AdaBoost.OC has shown to be an effective method in boosting "weak" binary classifiers for multi-class learning. It employs the Error Correcting Output Code (ECOC) method...
Rong Jin, Jian Zhang
111
Voted
ICML
2010
IEEE
15 years 1 months ago
Multi-Class Pegasos on a Budget
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Zhuang Wang, Koby Crammer, Slobodan Vucetic
113
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RIAO
2004
15 years 2 months ago
Unsupervised Learning with Term Clustering for Thematic Segmentation of Texts
In this paper we introduce a machine learning approach for automatic text segmentation. Our text segmenter clusters text-segments containing similar concepts. It first discovers th...
Marc Caillet, Jean-François Pessiot, Massih...
133
Voted

Publication
170views
14 years 11 months ago
Covariance Regularization for Supervised Learning in High Dimensions
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...
104
Voted
AAAI
2006
15 years 2 months ago
kFOIL: Learning Simple Relational Kernels
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FO...
Niels Landwehr, Andrea Passerini, Luc De Raedt, Pa...