This paper deals with finding outliers (exceptions) in large, multidimensional datasets. The identification of outliers can lead to the discovery of truly unexpected knowledge in ...
Multivariate images are now commonly produced in many applications. If their process is possible due to computers power and new programming languages, theoretical difficulties hav...
Multiple-dimensional, i.e., polyadic, data exist in many applications, such as personalized recommendation and multipledimensional data summarization. Analyzing all the dimensions...
We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...