Matrix factorization algorithms are frequently used in the machine learning community to find low dimensional representations of data. We introduce a novel generative Bayesian pro...
Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, hu...
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....
This paper addresses the problem of reconstructing surface models of indoor scenes from sparse 3D scene structure captured from N camera views. Sparse 3D measurements of real scen...
Anastasios Manessis, Adrian Hilton, Philip F. McLa...
Several molecular systems form large-scale objects. One would like to understand their assembly and how this assembly is regulated. As a first step, we investigate the phase trans...