The appearance of dynamic scenes is often largely governed by a latent low-dimensional dynamic process. We show how to learn a mapping from video frames to this lowdimensional rep...
Many optimisation problems contain substructures involving constraints on sequences of decision variables. Such constraints can be very complex to express with mixed integer progra...
The paper presents distributed and parallel -approximation algorithms for covering problems, where is the maximum number of variables on which any constraint depends (for example...
se a new abstraction for pointer analysis that represents reads and writes to memory instead of traditional points-to relations. Compared to points-to graphs, our Assign-Fetch Gra...
Marcio Buss, Daniel Brand, Vugranam C. Sreedhar, S...
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...