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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 11 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
KDD
2008
ACM
134views Data Mining» more  KDD 2008»
14 years 11 months ago
Privacy-preserving cox regression for survival analysis
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...
Shipeng Yu, Glenn Fung, Rómer Rosales, Srir...
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
14 years 11 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
2002
ACM
183views Data Mining» more  KDD 2002»
14 years 11 months ago
E-CAST: A Data Mining Algorithm for Gene Expression Data
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
STOC
2007
ACM
101views Algorithms» more  STOC 2007»
14 years 11 months ago
The price of privacy and the limits of LP decoding
This work is at the intersection of two lines of research. One line, initiated by Dinur and Nissim, investigates the price, in accuracy, of protecting privacy in a statistical dat...
Cynthia Dwork, Frank McSherry, Kunal Talwar