In Sequential Viterbi Models, such as HMMs, MEMMs, and Linear Chain CRFs, the type of patterns over output sequences that can be learned by the model depend directly on the modelā...
Probabilistic relational models are an eļ¬cient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
This paper studies a version of the job shop scheduling problem in which some operations have to be scheduled within non-relaxable time windows i.e. earliest latest possible start...
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
We present a method to analyze daily activities, such as meal preparation, using video from an egocentric camera. Our method performs inference about activities, actions, hands, a...