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» Approximation Methods for Supervised Learning
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160
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ML
2008
ACM
248views Machine Learning» more  ML 2008»
15 years 2 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
138
Voted
WWW
2009
ACM
16 years 2 months ago
Enhancing diversity, coverage and balance for summarization through structure learning
Document summarization plays an increasingly important role with the exponential growth of documents on the Web. Many supervised and unsupervised approaches have been proposed to ...
Liangda Li, Ke Zhou, Gui-Rong Xue, Hongyuan Zha, Y...
115
Voted
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
16 years 2 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
173
Voted
CVPR
2009
IEEE
16 years 9 months ago
Learning Semantic Visual Vocabularies Using Diffusion Distance
In this paper, we propose a novel approach for learning generic visual vocabulary. We use diffusion maps to au-tomatically learn a semantic visual vocabulary from ab-undant quantiz...
Jingen Liu (University of Central Florida), Yang Y...
109
Voted
WWW
2004
ACM
16 years 2 months ago
Unsupervised learning of soft patterns for generating definitions from online news
Breaking news often contains timely definitions and descriptions of current terms, organizations and personalities. We utilize such web sources to construct definitions for such t...
Hang Cui, Min-Yen Kan, Tat-Seng Chua