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Approximation Algorithms for Co-Clustering

Summary: First provable approximation algorithms for co-clustering: simple algorithms achieving constant-factor approximations for simultaneous row/column partitioning of matrices. Also prove co-clustering NP-hard, moving the problem from heuristics to rigorous algorithmic footing. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1460
Venue
PODS
Year
2008
Pagerank
4.3690661e-05
Overall Rank
9,257 | 35.61%
DOI
-

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Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
12,176 Effective Data Co-Reduction for Multimedia Similarity Search 2011 SIGMOD 4.1945683e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
4,187 Clustering via Matrix Powering 2004 PODS 6.3754336e-05
13,610 Programmable Clustering 2006 PODS -
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