Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
Abstract—This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discu...
Instead of selling advertisement spots one by one, some French satellite channels decided in 2002 to modify their commercial offer in order to sell packages of spots. These new g...
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Given a primal-dual pair of linear programs, it is well known that if their optimal values are viewed as lying on the extended real line, then the duality gap is zero, unless both...