We present a hierarchical classification model that allows rare objects to borrow statistical strength from related objects that have many training examples. Unlike many of the e...
Ruslan Salakhutdinov, Antonio Torralba, Josh Tenen...
We describe a mid-level approach for action recognition. From an input video, we extract salient spatio-temporal structures by forming clusters of trajectories that serve as candi...
We are interested in the simulation and optimization of gas transport in networks. Different regions of the network may be modelled by different equations. There are three models...
This paper explores a formulation for attributed graph matching as an inference problem over a hidden Markov Random Field. We approximate the fully connected model with simpler mo...
Dante Augusto Couto Barone, Terry Caelli, Tib&eacu...
We introduce in this paper two probabilistic reasoning models (PRM-1 and PRM-2) which combine the Principal Component Analysis (PCA) technique and the Bayes classifier and show th...