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» A New Indexing Method for High Dimensional Dataset
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SDM
2008
SIAM
117views Data Mining» more  SDM 2008»
15 years 2 months ago
A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
Yijun Sun, Sinisa Todorovic, Steve Goodison
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
15 years 9 months ago
Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets.
Large amounts of remotely sensed data calls for data mining techniques to fully utilize their rich information content. In this paper, we study new means of discovery and summariz...
Wei Ding 0003, Tomasz F. Stepinski, Josue Salazar
119
Voted
NIPS
1997
15 years 2 months ago
EM Algorithms for PCA and SPCA
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Sam T. Roweis
SDM
2004
SIAM
225views Data Mining» more  SDM 2004»
15 years 2 months ago
Active Semi-Supervision for Pairwise Constrained Clustering
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
Sugato Basu, Arindam Banerjee, Raymond J. Mooney
123
Voted
SIGIR
2005
ACM
15 years 6 months ago
Orthogonal locality preserving indexing
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
Deng Cai, Xiaofei He