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SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
14 years 11 months ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon
ACL
2007
14 years 11 months ago
Sparse Information Extraction: Unsupervised Language Models to the Rescue
Even in a massive corpus such as the Web, a substantial fraction of extractions appear infrequently. This paper shows how to assess the correctness of sparse extractions by utiliz...
Doug Downey, Stefan Schoenmackers, Oren Etzioni
ICML
2007
IEEE
15 years 10 months ago
Unsupervised prediction of citation influences
Publication repositories contain an abundance of information about the evolution of scientific research areas. We address the problem of creating a visualization of a research are...
Laura Dietz, Steffen Bickel, Tobias Scheffer
TNN
2010
143views Management» more  TNN 2010»
14 years 4 months ago
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
WACV
2005
IEEE
15 years 3 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee