Bayesian Model Averaging (BMA) is well known for improving predictive accuracy by averaging inferences over all models in the model space. However, Markov chain Monte Carlo (MCMC)...
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuch...
A method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multiscale curvature...
Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random w...
Recent research in frequent pattern mining (FPM) has shifted from obtaining the complete set of frequent patterns to generating only a representative (summary) subset of frequent ...