Quantum computers have demonstrable ability to solve problems at a scale beyond brute-
force classical simulation. Interest in quantum algorithms has developed in many areas …

In this paper, we analyze the convergence of the alternating direction method of multipliers
(ADMM) for minimizing a nonconvex and possibly nonsmooth objective function, ϕ (x_0 …

This paper proposes a robust design approach, based on eroded, intermediate and dilated
projections, to handle uniform manufacturing uncertainties in stress-constrained topology …

Stress‐constrained topology optimization requires techniques for handling thousands to
millions of stress constraints. This work presents a comprehensive numerical study …

Abstract We present Optimization Engine (OpEn): an open-source code generation
framework for real-time embedded nonconvex optimization, which implements a novel …

We consider optimization problems on manifolds with equality and inequality constraints. A
large body of work treats constrained optimization in Euclidean spaces. In this work, we …

In topology optimization, the treatment of stress constraints for very large scale problems
(more than 100 million elements and more than 600 million stress constraints) has so far not …

Before the execution of many standard graph signal processing (GSP) modules, such as
compression and restoration, learning of a graph that encodes pairwise (dis) similarities in …

We propose an algorithm for solving nonsmooth, nonconvex, constrained optimization
problems as well as a new set of visualization tools for comparing the performance of …

We propose a practical inexact augmented Lagrangian method (iALM) for nonconvex
problems with nonlinear constraints. We characterize the total computational complexity of …