The formalism of probabilistic graphical models provides a unifying framework for capturing
complex dependencies among random variables, and building large-scale multivariate …

Second-order cone programming (SOCP) problems are convex optimization problems in
which a linear function is minimized over the intersection of an affine linear manifold with the …

This survey covers the state of the art of techniques for solving general-purpose constrained
global optimization problems and continuous constraint satisfaction problems, with …

An approach for estimating the pose of a camera given a set of 3D points and their
corresponding 2D image projections is presented. It formulates the problem as a non-linear …

State-of-the-art research on MRFs, successful MRF applications, and advanced topics for
future study. This volume demonstrates the power of the Markov random field (MRF) in …

We introduce the Suggest-and-Improve framework for general nonconvex quadratically
constrained quadratic programs (QCQPs). Using this framework, we generalize a number of …

This paper surveys results on the NP-hard mixed-integer quadratically constrained
programming problem. The focus is strong convex relaxations and valid inequalities, which …

We present a method for finding exact solutions of Max-Cut, the problem of finding a cut of
maximum weight in a weighted graph. We use a Branch-and-Bound setting that applies a …

We consider relaxations for nonconvex quadratically constrained quadratic programming
(QCQP) based on semidefinite programming (SDP) and the reformulation-linearization …

This paper proposes a novel two-stage game-theoretic residential photovoltaic (PV) panels
planning framework for distribution grids with potential PV prosumers. One innovative …