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» Spectral Algorithms for Supervised Learning
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CIKM
2008
Springer
14 years 11 months ago
Semi-supervised text categorization by active search
In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...
ESWS
2008
Springer
14 years 11 months ago
Instance Based Clustering of Semantic Web Resources
Abstract. The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue t...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...
93
Voted
DGO
2007
152views Education» more  DGO 2007»
14 years 11 months ago
Identifying and classifying subjective claims
To understand the subjective documents, for example, public comments on the government’s proposed regulation, opinion identification and classification is required. Rather than ...
Namhee Kwon, Liang Zhou, Eduard H. Hovy, Stuart W....
IJCAI
2007
14 years 11 months ago
Explanation-Based Feature Construction
Choosing good features to represent objects can be crucial to the success of supervised machine learning algorithms. Good high-level features are those that concentrate informatio...
Shiau Hong Lim, Li-Lun Wang, Gerald DeJong
92
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NIPS
2003
14 years 11 months ago
Computing Gaussian Mixture Models with EM Using Equivalence Constraints
Density estimation with Gaussian Mixture Models is a popular generative technique used also for clustering. We develop a framework to incorporate side information in the form of e...
Noam Shental, Aharon Bar-Hillel, Tomer Hertz, Daph...