The goal of this paper is to analyze the intriguing instability of classifiers to adversarial
perturbations (Szegedy et al., in: International conference on learning representations …

The standard assumption for proving linear convergence of first order methods for smooth
convex optimization is the strong convexity of the objective function, an assumption which …

Variational Analysis of Regular Mappings Page 1 Springer Monographs in Mathematics
Variational Analysis of Regular Mappings Alexander D. Ioffe Theory and Applications Page 2 …

The primary aim of this book is to present the conjugate and subdifferential calculus using
the method of perturbation functions in order to obtain the most general results in this field …

Mathematical optimization has always been at the heart of engineering, statistics, and
economics. In these applied domains, optimization concepts and methods have often been …

Originated from the practical implementation and numerical considerations of iterative
methods for solving mathematical programs, the study of error bounds has grown and …

Nonlinear applied analysis and in particular the related? elds of continuous optimization and
variational inequality problems have gone through major developments over the last three …

In the present paper, we are concerned with conditions ensuring the exact penalty for
nonconvex programming. Firstly, we consider problems with concave objective and …

The strong conical hull intersection property and bounded linear regularity are properties of
a collection of finitely many closed convex intersecting sets in Euclidean space. These …

The paper presents a general classification scheme of necessary and sufficient criteria for
the error bound property incorporating the existing conditions. Several derivative-like objects …