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NIPS
2008
13 years 6 months ago
On the Reliability of Clustering Stability in the Large Sample Regime
Clustering stability is an increasingly popular family of methods for performing model selection in data clustering. The basic idea is that the chosen model should be stable under...
Ohad Shamir, Naftali Tishby
ICASSP
2011
IEEE
12 years 8 months ago
Interference alignment in clustered ad hoc networks: High reliability regime and per-cluster aloha
Wireless networks are fundamentally limited by the intensity of the received signals and the mutual interference caused by many concurrent transmissions. We consider large wireles...
Roland Tresch, Giusi Alfano, Maxime Guillaud
ICML
2006
IEEE
14 years 5 months ago
An investigation of computational and informational limits in Gaussian mixture clustering
We investigate under what conditions clustering by learning a mixture of spherical Gaussians is (a) computationally tractable; and (b) statistically possible. We show that using p...
Nathan Srebro, Gregory Shakhnarovich, Sam T. Rowei...
COLT
2006
Springer
13 years 8 months ago
A Sober Look at Clustering Stability
Stability is a common tool to verify the validity of sample based algorithms. In clustering it is widely used to tune the parameters of the algorithm, such as the number k of clust...
Shai Ben-David, Ulrike von Luxburg, Dávid P...
ML
2010
ACM
127views Machine Learning» more  ML 2010»
13 years 2 months ago
Stability and model selection in k-means clustering
Abstract Clustering Stability methods are a family of widely used model selection techniques for data clustering. Their unifying theme is that an appropriate model should result in...
Ohad Shamir, Naftali Tishby