We present a principled Bayesian framework for modeling partial memberships of data points to clusters. Unlike a standard mixture model which assumes that each data point belongs ...
Katherine A. Heller, Sinead Williamson, Zoubin Gha...
Abstract. This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a se...
Abstract. Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies i...
Zhiyuan Yao, Annika H. Holmbom, Tomas Eklund, Barb...
Corpus-based grammar induction generally relies on hand-parsed training data to learn the structure of the language. Unfortunately, the cost of building large annotated corpora is...
Abstract. Monitoring large distributed concurrent systems is a challenging task. In this paper we formulate (model-based) diagnosis by means of hidden state history reconstruction,...