At the heart of many scientific conferences is the problem of matching submitted papers to suitable reviewers. Arriving at a good assignment is a major and important challenge fo...
Laurent Charlin, Richard S. Zemel, Craig Boutilier
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
We study power control in multicell CDMA wireless networks as a team optimization problem where each mobile attains at the minimum its individual fixed target SIR level and beyon...
Tansu Alpcan, Xingzhe Fan, Tamer Basar, Murat Arca...
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...