We develop regression diagnostics for functional regression models which relate a functional response to predictor variables that can be multivariate vectors or random functions. ...
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Abstract. Stimulus4ependent changes have been observed in the correlations between the spike trains of simultaneously-recorded pairs of neurons from the auditory cortex of marmoset...
A nonlinear dynamic model for the quotes issued by Nasdaq dealers is considered, focussing on the top two Electronic Communication Networks (ECNs), Island and Instinet, and the th...