In this work we present a unified view on Markov random fields and recently proposed continuous tight convex relaxations for multi-label assignment in the image plane. These rel...
Incorporating invariances into a learning algorithm is a common problem in machine learning. We provide a convex formulation which can deal with arbitrary loss functions and arbit...
Choon Hui Teo, Amir Globerson, Sam T. Roweis, Alex...
In Combinatorial Public Projects, there is a set of projects that may be undertaken, and a set of selfinterested players with a stake in the set of projects chosen. A public plann...
We study a new class of decentralized algorithms for discrete optimization via simulation, which is inspired by the fictitious play algorithm applied to games with identical inte...
The solution to a Nash or a nonsymmetric bargaining game is obtained by maximizing a concave function over a convex set, i.e., it is the solution to a convex program. We show that...