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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 9 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 9 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
2004
ACM
109views Data Mining» more  KDD 2004»
14 years 9 months ago
Identifying early buyers from purchase data
Market research has shown that consumers exhibit a variety of different purchasing behaviors; specifically, some tend to purchase products earlier than other consumers. Identifyin...
Paat Rusmevichientong, Shenghuo Zhu, David Selinge...
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
14 years 9 months ago
The data mining approach to automated software testing
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...
Mark Last, Menahem Friedman, Abraham Kandel
KDD
2003
ACM
142views Data Mining» more  KDD 2003»
14 years 9 months ago
Frequent-subsequence-based prediction of outer membrane proteins
A number of medically important disease-causing bacteria (collectively called Gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell....
Rong She, Fei Chen 0002, Ke Wang, Martin Ester, Je...
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