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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 7 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
2006
ACM
201views Data Mining» more  KDD 2006»
16 years 7 months ago
Clustering based large margin classification: a scalable approach using SOCP formulation
This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture...
J. Saketha Nath, Chiranjib Bhattacharyya, M. Naras...
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
16 years 7 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
16 years 7 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
STOC
2003
ACM
152views Algorithms» more  STOC 2003»
16 years 7 months ago
Reducing truth-telling online mechanisms to online optimization
We describe a general technique for converting an online algorithm B to a truthtelling mechanism. We require that the original online competitive algorithm has certain "nicen...
Baruch Awerbuch, Yossi Azar, Adam Meyerson
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