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» Consistent Minimization of Clustering Objective Functions
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ICML
2006
IEEE
16 years 12 days ago
A continuation method for semi-supervised SVMs
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
Olivier Chapelle, Mingmin Chi, Alexander Zien
ICASSP
2011
IEEE
14 years 3 months ago
Low-rank matrix completion with geometric performance guarantees
—The low-rank matrix completion problem can be stated as follows: given a subset of the entries of a matrix, find a low-rank matrix consistent with the observations. There exist...
Wei Dai, Ely Kerman, Olgica Milenkovic
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
15 years 1 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
84
Voted
PAKDD
2010
ACM
198views Data Mining» more  PAKDD 2010»
15 years 4 months ago
A Better Strategy of Discovering Link-Pattern Based Communities by Classical Clustering Methods
Abstract. The definition of a community in social networks varies with applications. To generalize different types of communities, the concept of linkpattern based community was pr...
Chen-Yi Lin, Jia-Ling Koh, Arbee L. P. Chen
FSKD
2005
Springer
77views Fuzzy Logic» more  FSKD 2005»
15 years 5 months ago
Knowledge Structuring and Evaluation Based on Grey Theory
It is important nowadays to provide guidance for individuals or organizations to improve their knowledge according to their objectives, especially in the case of incomplete cogniti...
Chen Huang, Yushun Fan