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KDD
2009
ACM
188views Data Mining» more  KDD 2009»
16 years 6 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
16 years 6 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
KDD
2005
ACM
182views Data Mining» more  KDD 2005»
16 years 6 months ago
Making holistic schema matching robust: an ensemble approach
The Web has been rapidly "deepened" by myriad searchable databases online, where data are hidden behind query interfaces. As an essential task toward integrating these m...
Bin He, Kevin Chen-Chuan Chang
KDD
2001
ACM
203views Data Mining» more  KDD 2001»
16 years 6 months ago
Ensemble-index: a new approach to indexing large databases
The problem of similarity search (query-by-content) has attracted much research interest. It is a difficult problem because of the inherently high dimensionality of the data. The ...
Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
POPL
2006
ACM
16 years 6 months ago
A hierarchical model of data locality
In POPL 2002, Petrank and Rawitz showed a universal result-finding optimal data placement is not only NP-hard but also impossible to approximate within a constant factor if P = NP...
Chengliang Zhang, Chen Ding, Mitsunori Ogihara, Yu...