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» Measuring the Quality of Approximated Clusterings
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SODA
2010
ACM
149views Algorithms» more  SODA 2010»
16 years 3 months ago
Sharp kernel clustering algorithms and their associated Grothendieck inequalities
abstract Subhash Khot Assaf Naor In the kernel clustering problem we are given a (large) n ? n symmetric positive semidefinite matrix A = (aij) with n i=1 n j=1 aij = 0 and a (sma...
Subhash Khot, Assaf Naor
FOGA
2011
14 years 9 months ago
The logarithmic hypervolume indicator
It was recently proven that sets of points maximizing the hypervolume indicator do not give a good multiplicative approximation of the Pareto front. We introduce a new “logarith...
Tobias Friedrich, Karl Bringmann, Thomas Voß...
EDBT
2004
ACM
142views Database» more  EDBT 2004»
16 years 6 months ago
Iterative Incremental Clustering of Time Series
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
ICPP
2002
IEEE
15 years 11 months ago
Optimal Video Replication and Placement on a Cluster of Video-on-Demand Servers
A cost-effective approach to building up scalable Videoon-Demand (VoD) servers is to couple a number of VoD servers together in a cluster. In this article, we study a crucial vide...
Xiaobo Zhou, Cheng-Zhong Xu
ISI
2008
Springer
15 years 6 months ago
Probabilistic frameworks for privacy-aware data mining
Often several cooperating parties would like to have a global view of their joint data for various data mining objectives, but cannot reveal the contents of individual records due...
Joydeep Ghosh