We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
We consider the issue of representing coalitional games in multiagent systems with externalities (i.e., in systems where the performance of one coalition may be affected by other ...
Tomasz P. Michalak, Talal Rahwan, Jacek Sroka, And...
A whole variety of different techniques for simulating global illumination in virtual environments have been developed over recent years. Each technique, including Radiosity, Mont...
Philipp Slusallek, Marc Stamminger, Wolfgang Heidr...
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...