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KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 10 months ago
Automatic identification of quasi-experimental designs for discovering causal knowledge
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
KDD
2007
ACM
197views Data Mining» more  KDD 2007»
14 years 10 months ago
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
Jieping Ye, Shuiwang Ji, Jianhui Chen
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 10 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
KDD
2006
ACM
128views Data Mining» more  KDD 2006»
14 years 10 months ago
On privacy preservation against adversarial data mining
Privacy preserving data processing has become an important topic recently because of advances in hardware technology which have lead to widespread proliferation of demographic and...
Charu C. Aggarwal, Jian Pei, Bo Zhang 0002
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
14 years 10 months ago
The "DGX" distribution for mining massive, skewed data
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Zhiqiang Bi, Christos Faloutsos, Flip Korn