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KDD
2006
ACM
115views Data Mining» more  KDD 2006»
16 years 7 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...
KDD
2005
ACM
170views Data Mining» more  KDD 2005»
16 years 7 months ago
Parallel mining of closed sequential patterns
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
Shengnan Cong, Jiawei Han, David A. Padua
KDD
2004
ACM
135views Data Mining» more  KDD 2004»
16 years 7 months ago
Discovering additive structure in black box functions
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Giles Hooker
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
16 years 7 months ago
Eigenspace-based anomaly detection in computer systems
We report on an automated runtime anomaly detection method at the application layer of multi-node computer systems. Although several network management systems are available in th...
Hisashi Kashima, Tsuyoshi Idé
KDD
2004
ACM
145views Data Mining» more  KDD 2004»
16 years 7 months ago
Mining coherent gene clusters from gene-sample-time microarray data
Extensive studies have shown that mining microarray data sets is important in bioinformatics research and biomedical applications. In this paper, we explore a novel type of genesa...
Daxin Jiang, Jian Pei, Murali Ramanathan, Chun Tan...
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