We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Neurophysiology reveals the properties of individual mirror neurons in the macaque while brain imaging reveals the presence of `mirror systems' (not individual neurons) in th...
Despite the large number of papers on network topology modeling and inference, there still exists ambiguity about the real nature of the Internet AS and router level topology. Whi...
Hamed Haddadi, Steve Uhlig, Andrew W. Moore, Richa...