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185
Voted
ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
Many clustering algorithms only find one clustering solution. However, data can often be grouped and interpreted in many different ways. This is particularly true in the high-dim...
199
Voted
KDD
2009
ACM
16 years 7 months ago
2009
ACM
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...
178
Voted
ICML
2007
IEEE
16 years 7 months ago
2007
IEEE
We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...
164
Voted
ACL
2006
15 years 7 months ago
2006
This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. I...
207
Voted
UAI
2003
15 years 7 months ago
2003
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...