The problem of synthesizing multivariate stationary series Y [n] = (Y1[n], . . . , YP [n])T , n ∈ Z, with prescribed non-Gaussian marginal distributions, and a targeted covarian...
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
We explore different approaches for performing hypothesis tests on the shape of a mean function by developing general methodologies both, for the often assumed, i.i.d. error struc...
In this contribution, we study companies engaging in B2C-E-Commerce and their ability to manage the relationship with their customers. We refer to this as companies’ ECCRM-capab...
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...