The current issue of the Machine Learning journal on "Theoretical
Advances in Data Clustering" is now freely available to all for only
the next 6 months. To view articles in the issue, please visit
http://www.kluweronline.com/issn/0885-6125
and select "Current Issue".
- -Nina
Table of Contents:
Introduction: Special Issue on Theoretical Advances in Data Clustering
Nina Mishra, Rajeev Motwani
Clustering Large Graphs via the Singular Value Decomposition
P. Drineas, A. Frieze, R. Kannan, S. Vempala, V. Vinay
Optimal Time Bounds for Approximate Clustering
Ramgopal R. Mettu, C. Greg Plaxton
A k-Median Algorithm with Running Time Independent of Data Size
Adam Meyerson, Liadan O'Callaghan, Serge Plotkin
Correlation Clustering
Nikhil Bansal, Avrim Blum, Shuchi Chawla
A New Conceptual Clustering Framework
Nina Mishra, Dana Ron, Ram Swaminathan
Subquadratic Approximation Algorithms for Clustering Problems in High
Dimensional Spaces
Allan Borodin, Rafail Ostrovsky, Yuval Rabani
Central Clustering of Attributed Graphs
Brijnesh J. Jain, Fritz Wysotzki
Semi-Supervised Learning on Riemannian Manifolds
Mikhail Belkin, Partha Niyogi
