International audienceWe discuss the application of random projections to conic programming: notably linear, second-order and semidefinite programs. We prove general approximation results on feasibility and optimality using the framework of formally real Jordan algebras. We then discuss some computational experiments on randomly generated semidefinite programs in order to illustrate the practical applicability of our ideas
Linear programming (LP) problems are commonly used in analysis and resource allocation, frequently s...
Convex conic programming is a general optimization model which includes linear, second-order-cone an...
Abstract. In this paper, we present a simple, yet useful, concentration result concerning random (we...
International audienceWe discuss the application of random projections to conic programming: notably...
Random projections can reduce the dimensionality of point sets while keeping approximate congruence....
International audienceRandom projections can reduce the dimensionality of point sets while keeping a...
International audienceThe use of random projections in mathematical programming allows standard solu...
International audienceRandom projections are random matrices that can be used to perform dimensional...
We present a novel algorithm, Random Conic Pursuit, that solves semidefinite pro-grams (SDPs) via re...
International audienceRandom projections decrease the dimensionality of a finite set of vectors whil...
International audienceRandom projections map a set of points in a high dimensional space to a lower ...
International audienceRandom projections are used as dimensional reduction techniques in many situat...
Random projection is a simple geometric technique for reducing the dimensionality of a set of points...
International audienceOne way to solve very large linear programs in standard form is to apply a ran...
Linear programming (LP) problems are commonly used in analysis and resource allocation, frequently s...
Convex conic programming is a general optimization model which includes linear, second-order-cone an...
Abstract. In this paper, we present a simple, yet useful, concentration result concerning random (we...
International audienceWe discuss the application of random projections to conic programming: notably...
Random projections can reduce the dimensionality of point sets while keeping approximate congruence....
International audienceRandom projections can reduce the dimensionality of point sets while keeping a...
International audienceThe use of random projections in mathematical programming allows standard solu...
International audienceRandom projections are random matrices that can be used to perform dimensional...
We present a novel algorithm, Random Conic Pursuit, that solves semidefinite pro-grams (SDPs) via re...
International audienceRandom projections decrease the dimensionality of a finite set of vectors whil...
International audienceRandom projections map a set of points in a high dimensional space to a lower ...
International audienceRandom projections are used as dimensional reduction techniques in many situat...
Random projection is a simple geometric technique for reducing the dimensionality of a set of points...
International audienceOne way to solve very large linear programs in standard form is to apply a ran...
Linear programming (LP) problems are commonly used in analysis and resource allocation, frequently s...
Convex conic programming is a general optimization model which includes linear, second-order-cone an...
Abstract. In this paper, we present a simple, yet useful, concentration result concerning random (we...