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150
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PAKDD
2000
ACM
124views Data Mining» more  PAKDD 2000»
15 years 7 months ago
Feature Selection for Clustering
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Manoranjan Dash, Huan Liu
KDD
2001
ACM
181views Data Mining» more  KDD 2001»
16 years 3 months ago
Co-clustering documents and words using bipartite spectral graph partitioning
Both document clustering and word clustering are well studied problems. Most existing algorithms cluster documents and words separately but not simultaneously. In this paper we pr...
Inderjit S. Dhillon
108
Voted
ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
15 years 9 months ago
Learning by Propagability
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
133
Voted
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
15 years 4 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
CDC
2009
IEEE
285views Control Systems» more  CDC 2009»
15 years 1 months ago
Adaptive randomized algorithm for finding eigenvector of stochastic matrix with application to PageRank
Abstract-- The problem of finding the eigenvector corresponding to the largest eigenvalue of a stochastic matrix has numerous applications in ranking search results, multi-agent co...
Alexander V. Nazin, Boris T. Polyak