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» Approximation Algorithms for Data Placement Problems
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SODA
2008
ACM
126views Algorithms» more  SODA 2008»
13 years 9 months ago
On distributing symmetric streaming computations
A common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. For truly massive data sets, howeve...
Jon Feldman, S. Muthukrishnan, Anastasios Sidiropo...
KDD
2006
ACM
163views Data Mining» more  KDD 2006»
14 years 8 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper
SIAMCOMP
2002
152views more  SIAMCOMP 2002»
13 years 7 months ago
Maintaining Stream Statistics over Sliding Windows
We consider the problem of maintaining aggregates and statistics over data streams, with respect to the last N data elements seen so far. We refer to this model as the sliding wind...
Mayur Datar, Aristides Gionis, Piotr Indyk, Rajeev...
ICDM
2008
IEEE
108views Data Mining» more  ICDM 2008»
14 years 2 months ago
Non-negative Matrix Factorization on Manifold
Recently Non-negative Matrix Factorization (NMF) has received a lot of attentions in information retrieval, computer vision and pattern recognition. NMF aims to find two non-nega...
Deng Cai, Xiaofei He, Xiaoyun Wu, Jiawei Han
KDD
1997
ACM
154views Data Mining» more  KDD 1997»
13 years 11 months ago
Autonomous Discovery of Reliable Exception Rules
This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
Einoshin Suzuki