We present a two-phase algorithm for solving large-scale quadratic programs (QPs). In the first phase, gradient-projection iterations approximately minimize an augmented Lagrangian...
In this paper we consider the problem of solving different pose and registration problems under rotational constraints. Traditionally, methods such as the iterative closest point ...
We propose a modified alternate direction method for solving convex quadratically constrained quadratic semidefinite optimization problems. The method is a first-order method, the...
This paper presents a Newton-like algorithm for solving systems of rank constrained linear matrix inequalities. Though local quadratic convergence of the algorithm is not a priori...
Abstract. Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for...
Ernesto E. Prudencio, Richard H. Byrd, Xiao-Chuan ...