Add to ORKGInternational audienceRandom projections can reduce the dimensionality of point sets while keeping approximate congruence. Applying random projections to optimization problems raises many theoretical and computational issues. Most of the theoretical issues in the application of random projections to conic programming were addressed in [1]. This paper focuses on semidefinite programming
There has been considerable interest in random projections, an approximate algorithm for estimating ...
Random projection is a technique of mapping a number of points in a high-dimensional space into a lo...
Linear function approximations based on random projections are proposed and justified for a class of...
International audienceRandom projections can reduce the dimensionality of point sets while keeping a...
Random projections can reduce the dimensionality of point sets while keeping approximate congruence....
International audienceWe discuss the application of random projections to conic programming: notably...
International audienceRandom projections are random matrices that can be used to perform dimensional...
International audienceRandom projections decrease the dimensionality of a finite set of vectors whil...
We present a novel algorithm, Random Conic Pursuit, that solves semidefinite pro-grams (SDPs) via re...
International audienceThe use of random projections in mathematical programming allows standard solu...
Random projection is a simple geometric technique for reducing the dimensionality of a set of points...
International audienceRandom projections are used as dimensional reduction techniques in many situat...
International audienceRandom projections map a set of points in a high dimensional space to a lower ...
With the advent of massive datasets, statistical learning and information processing techniques are ...
We propose methods for improving both the accuracy and efficiency of random projections, the pop...
There has been considerable interest in random projections, an approximate algorithm for estimating ...
Random projection is a technique of mapping a number of points in a high-dimensional space into a lo...
Linear function approximations based on random projections are proposed and justified for a class of...
International audienceRandom projections can reduce the dimensionality of point sets while keeping a...
Random projections can reduce the dimensionality of point sets while keeping approximate congruence....
International audienceWe discuss the application of random projections to conic programming: notably...
International audienceRandom projections are random matrices that can be used to perform dimensional...
International audienceRandom projections decrease the dimensionality of a finite set of vectors whil...
We present a novel algorithm, Random Conic Pursuit, that solves semidefinite pro-grams (SDPs) via re...
International audienceThe use of random projections in mathematical programming allows standard solu...
Random projection is a simple geometric technique for reducing the dimensionality of a set of points...
International audienceRandom projections are used as dimensional reduction techniques in many situat...
International audienceRandom projections map a set of points in a high dimensional space to a lower ...
With the advent of massive datasets, statistical learning and information processing techniques are ...
We propose methods for improving both the accuracy and efficiency of random projections, the pop...
There has been considerable interest in random projections, an approximate algorithm for estimating ...
Random projection is a technique of mapping a number of points in a high-dimensional space into a lo...
Linear function approximations based on random projections are proposed and justified for a class of...