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» Information Preserving Dimensionality Reduction
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CIKM
2010
Springer
13 years 8 months ago
Decomposing background topics from keywords by principal component pursuit
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Kerui Min, Zhengdong Zhang, John Wright, Yi Ma
CCS
2004
ACM
14 years 3 months ago
Comparing the expressive power of access control models
Comparing the expressive power of access control models is recognized as a fundamental problem in computer security. Such comparisons are generally based on simulations between di...
Mahesh V. Tripunitara, Ninghui Li
GEOINFORMATICA
1998
125views more  GEOINFORMATICA 1998»
13 years 9 months ago
Computational Perspectives on Map Generalization
ally related entity types, or classes, into higher level, more abstract types, as part of a hierarchical classi®cation scheme. graphy, generalization retains the notion of abstrac...
Robert Weibel, Christopher B. Jones
KDD
2006
ACM
115views Data Mining» more  KDD 2006»
14 years 10 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
CIKM
2006
Springer
14 years 1 months ago
Structure-based querying of proteins using wavelets
The ability to retrieve molecules based on structural similarity has use in many applications, from disease diagnosis and treatment to drug discovery and design. In this paper, we...
Keith Marsolo, Srinivasan Parthasarathy, Kotagiri ...