In this paper, we propose a novel approach to model shape variations. It encodes sparsity, exploits geometric redundancy, and accounts for the different degrees of local variation...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Understanding intents from search queries can improve a user’s search experience and boost a site’s advertising profits. Query tagging via statistical sequential labeling mode...
Ye-Yi Wang, Raphael Hoffmann, Xiao Li, Jakub Szyma...
This paper deals with estimation of dense optical flow
and ego-motion in a generalized imaging system by exploiting
probabilistic linear subspace constraints on the flow.
We dea...
Richard Roberts (Georgia Institute of Technology),...
Background: Many proteomics initiatives require a seamless bioinformatics integration of a range of analytical steps between sample collection and systems modeling immediately ass...
Romesh Stanislaus, Liu Hong Jiang, Martha Swartz, ...