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SAC
2005
ACM
15 years 10 months ago
Discovering parametric clusters in social small-world graphs
We present a strategy for analyzing large, social small-world graphs, such as those formed by human networks. Our approach brings together ideas from a number of different resear...
Jonathan McPherson, Kwan-Liu Ma, Michael Ogawa
ECML
2001
Springer
15 years 9 months ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon
EUROSYS
2011
ACM
14 years 8 months ago
Scarlett: coping with skewed content popularity in mapreduce clusters
To improve data availability and resilience MapReduce frameworks use file systems that replicate data uniformly. However, analysis of job logs from a large production cluster show...
Ganesh Ananthanarayanan, Sameer Agarwal, Srikanth ...
164
Voted
ICML
2007
IEEE
16 years 6 months ago
Maximum margin clustering made practical
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
Kai Zhang, Ivor W. Tsang, James T. Kwok
155
Voted
ICML
2007
IEEE
16 years 6 months ago
Cluster analysis of heterogeneous rank data
Cluster analysis of ranking data, which occurs in consumer questionnaires, voting forms or other inquiries of preferences, attempts to identify typical groups of rank choices. Emp...
Ludwig M. Busse, Peter Orbanz, Joachim M. Buhmann