: We present a practical approach to nonparametric cluster analysis of large data sets. The number of clusters and the cluster centres are automatically derived by mode seeking wit...
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
A stochastic formulation of the Analytic Hierarchy Process (AHP) using an approach based on Bayesian categorical data models has been developed. However, in categorical data model...
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...