Background: The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compa...
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, w...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
We propose a new approach to semi-supervised clustering that utilizes boosting to simultaneously learn both a similarity measure and a clustering of the data from given instancele...