This paper reviews the vast literature on static output feedback design for linear time-
invariant systems including classical results and recent developments. In particular, we …

This article reviews the gradient sampling methodology for solving nonsmooth, nonconvex
optimization problems. We state an intuitively straightforward gradient sampling algorithm …

Deep neural networks (DNNs) have demonstrated dominating performance in many fields;
since AlexNet, networks used in practice are going wider and deeper. On the theoretical …

Nonsmooth nonconvex optimization problems broadly emerge in machine learning and
business decision making, whereas two core challenges impede the development of …

Variational analysis has been recognized as a fruitful area in mathematics that on the one
hand deals with the study of optimization and equilibrium problems and on the other hand …

To reduce fuel consumption and emissions in plug-in hybrid electric vehicles (PHEVs), it is
equally important to select an appropriate drive train topology as it is to develop a suitable …

Nonconvex optimization arises in many areas of computational science and engineering.
However, most nonconvex optimization algorithms are only known to have local …

We develop nonsmooth optimization techniques to solve H∞ synthesis problems under
additional structural constraints on the controller. Our approach avoids the use of Lyapunov …

We investigate the behavior of quasi-Newton algorithms applied to minimize a nonsmooth
function f, not necessarily convex. We introduce an inexact line search that generates a …

We establish the following result: If the graph of a lower semicontinuous real-extended-
valued function f:R^n→R∪{+∞\} admits a Whitney stratification (so in particular if f is a …