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» Approximation Algorithms for Data Placement Problems
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ALENEX
2008
142views Algorithms» more  ALENEX 2008»
13 years 9 months ago
Consensus Clustering Algorithms: Comparison and Refinement
Consensus clustering is the problem of reconciling clustering information about the same data set coming from different sources or from different runs of the same algorithm. Cast ...
Andrey Goder, Vladimir Filkov
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
14 years 8 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
14 years 8 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
PODS
2003
ACM
143views Database» more  PODS 2003»
14 years 8 months ago
Maintaining variance and k-medians over data stream windows
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
Brian Babcock, Mayur Datar, Rajeev Motwani, Liadan...
ISPD
2010
ACM
163views Hardware» more  ISPD 2010»
14 years 2 months ago
A statistical framework for designing on-chip thermal sensing infrastructure in nano-scale systems
Thermal/power issues have become increasingly important with more and more transistors being put on a single chip. Many dynamic thermal/power management techniques have been propo...
Yufu Zhang, Bing Shi, Ankur Srivastava