Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent ad...
We present a novel framework for recognizing repetitive
sequential events performed by human actors with strong
temporal dependencies and potential parallel overlap. Our
solutio...
Nuclear magnetic resonance (NMR) spectroscopy allows scientists to study protein structure, dynamics and interactions in solution. A necessary first step for such applications is ...
Chris Bailey-Kellogg, Sheetal Chainraj, Gopal Pand...
We present a method of distributed model checking of multiagent systems specified by a branching-time temporal-epistemic logic. We introduce a serial algorithm, central to the dis...