We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
The latent class model or multivariate multinomial mixture is a powerful model for clustering discrete data. This model is expected to be useful to represent non-homogeneous popula...
Damien Tessier, Marc Schoenauer, Christophe Bierna...
To discover patterns in historical data, climate scientists have applied various clustering methods with the goal of identifying regions that share some common climatological beha...
Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. ...
In this paper, we propose an efficient and effective method to find arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set of possi...
Let G be a graph containing N disjoint t-spanners that are inter-connected with M edges. We present an algorithm that constructs a data structure of size O(M2 + n log n) that answ...
Mattias Andersson, Joachim Gudmundsson, Christos L...