Publications

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".

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