The classical Frank and Wolfe theorem states that a quadratic function which is bounded below on a convex polyhedron $P$ attains its infimum on $P$. In this joint work with D. Noll and W. Sosa we investigate whether more general classes of convex sets can be identified which have this Frank-and-Wolfe property. We show that the intrinsic characterizations of Frank-and-Wolfe sets hinge on asymptotic properties of these sets.Non UBCUnreviewedAuthor affiliation: Universitat Autònoma de BarcelonaFacult
International audienceWe extend the Frank-Wolfe (FW) optimization algorithm to solve constrained smo...
6 pagesWe give a simple proof that the Frank-Wolfe algorithm obtains a stationary point at a rate of...
In this paper we consider the problem of minimizing a (possibly nonconvex) quadratic function with a...
International audienceThe classical Frank and Wolfe theorem states that a quadratic function which i...
In this paper we consider optimization problems defined by a quadraticobjective function and a finit...
A classical result due to Frank and Wolfe (1956) says that a quadratic function $f$ attains its supr...
Abstract. The famous Frank–Wolfe theorem ensures attainability of the op-timal value for quadratic o...
Abstract In this paper we consider optimization problems dened by a quadratic objective function an...
We revisit the Frank-Wolfe (FW) optimization under strongly convex constraint sets. We provide a fas...
The Frank-Wolfe algorithm is a popular method for minimizing a smooth convex function $f$ over a com...
We describe a common extension of the fundamental theorem of Linear Programming on the existence of ...
International audienceMany real-world problems can often be cast as the optimization of DR-submodula...
The fundamental theorem of linear programming (LP) states that every feasible linear program that is...
Using a known result on minimization of convex functionals on polyhedral cones, the Frank–Wolfe theo...
International audienceThe Frank-Wolfe (FW) optimization algorithm has lately re-gained popularity th...
International audienceWe extend the Frank-Wolfe (FW) optimization algorithm to solve constrained smo...
6 pagesWe give a simple proof that the Frank-Wolfe algorithm obtains a stationary point at a rate of...
In this paper we consider the problem of minimizing a (possibly nonconvex) quadratic function with a...
International audienceThe classical Frank and Wolfe theorem states that a quadratic function which i...
In this paper we consider optimization problems defined by a quadraticobjective function and a finit...
A classical result due to Frank and Wolfe (1956) says that a quadratic function $f$ attains its supr...
Abstract. The famous Frank–Wolfe theorem ensures attainability of the op-timal value for quadratic o...
Abstract In this paper we consider optimization problems dened by a quadratic objective function an...
We revisit the Frank-Wolfe (FW) optimization under strongly convex constraint sets. We provide a fas...
The Frank-Wolfe algorithm is a popular method for minimizing a smooth convex function $f$ over a com...
We describe a common extension of the fundamental theorem of Linear Programming on the existence of ...
International audienceMany real-world problems can often be cast as the optimization of DR-submodula...
The fundamental theorem of linear programming (LP) states that every feasible linear program that is...
Using a known result on minimization of convex functionals on polyhedral cones, the Frank–Wolfe theo...
International audienceThe Frank-Wolfe (FW) optimization algorithm has lately re-gained popularity th...
International audienceWe extend the Frank-Wolfe (FW) optimization algorithm to solve constrained smo...
6 pagesWe give a simple proof that the Frank-Wolfe algorithm obtains a stationary point at a rate of...
In this paper we consider the problem of minimizing a (possibly nonconvex) quadratic function with a...