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» Approximation algorithms for co-clustering
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JMLR
2010
179views more  JMLR 2010»
14 years 4 months ago
PAC-Bayesian Analysis of Co-clustering and Beyond
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
Yevgeny Seldin, Naftali Tishby
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
15 years 10 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...
190
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SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 8 days ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
ALGORITHMICA
2011
14 years 1 months ago
Approximating Minimum-Power Degree and Connectivity Problems
Guy Kortsarz, Vahab S. Mirrokni, Zeev Nutov, Elena...