Semidefinite programming relaxations through quadratic reformulation for box-constrained polynomial optimization problems

Our contribution is four-fold: (1) we propose a model with priors for multi-label classification allowing attractive as well as repulsive weights, (2) we cast the learning of this

The next section focus on the impact of compu- ting the clique decomposition on SDP relaxations of ACOPF problems formulated in complex variables or on SDP relaxations of ACOPF

Second, as rRLT constraint generation depends on an arbitrary choice (the basis of a certain matrix) we show how to choose this basis in such a way as to yield a more compact

Pierre Kunz, géologue, nous rejoint et nous empruntons alors le chemin menant au secteur entièrement aménagé par l’Association des Amis des Granges et du Biolley ( AAGB ) dans

Index Terms—Electro-quasi static field problem, electrostatic field model, forced vibration analysis, modal analysis, numerical model, piezoelectric transformer, plasma generation..

Keywords: box-constrained global optimization, polynomial optimization, Jackson kernel, semidefinite programming, generalized eigenvalue problem, sum-of-squares polynomial..

Our scheme for problems with a convex lower-level problem involves solving a transformed equivalent single-level problem by a sequence of SDP relaxations, whereas our approach

We investigate the optimal conditions of exact clustering recovery with high probability and show optimal performances – including in high dimensions, improving on [15], as well