We consider the problem of quantizing data generated from disparate sources, e.g. subjects performing actions with different styles, movies with particular genre bias, various con...
Ekaterina Taralova, Fernando DelaTorre, Martial He...
Frequent itemset mining has been the subject of a lot of work in data mining research ever since association rules were introduced. In this paper we address a problem with frequen...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
We develop a computational model of shape that extends existing Riemannian models of shape of curves to multidimensional objects of general topological type. We construct shape sp...
Xiuwen Liu, Yonggang Shi, Ivo D. Dinov, Washington...
Abstract. Real-world optimization problems are often subject to uncertainties, which can arise regarding stochastic model parameters, objective functions and decision variables. Th...