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In this paper, an upper semismooth function is defined to be a lower semicontinuous function whose radial subderivative satisfies a mild directional upper semicontinuity property. Examples of upper semismooth functions are the proper lower…

Optimization and Control · Mathematics 2017-03-10 Marc Lassonde

Submodular Functions are a special class of set functions, which generalize several information-theoretic quantities such as entropy and mutual information [1]. Submodular functions have subgradients and subdifferentials [2] and admit…

Discrete Mathematics · Computer Science 2020-07-01 Rishabh Iyer , Jeff Bilmes

We introduce a proximal subdifferential and develop a calculus for nonsmooth functions defined on any Riemannian manifold $M$. We give several applications of this theory, concerning: 1) differentiability and geometrical properties of the…

Differential Geometry · Mathematics 2007-05-23 Daniel Azagra , Juan Ferrera

In this paper, we first study nonsmooth steepest descent method for nonsmooth functions defined on Hilbert space and establish the corresponding algorithm by proximal subgradients. Then, we use this algorithm to find stationary points for…

Optimization and Control · Mathematics 2015-02-25 Zhou Wei , Qing Hai He

The subdifferential of a function is a generalization for nonsmooth functions of the concept of gradient. It is frequently used in variational analysis, particularly in the context of nonsmooth optimization. The present work proposes…

Optimization and Control · Mathematics 2016-09-13 Charles Audet , Warren Hare

The paper is devoted to developing subdifferential theory for set-valued mappings taking values in ordered infinite-dimensional spaces. This study is motivated by applications to problems of vector and set optimization with various…

Optimization and Control · Mathematics 2024-10-16 Boris S. Mordukhovich , Oanh Nguyen

The recent results of An, Luan, and Yen [Differential stability in convex optimization via generalized polyhedrality. Vietnam J. Math. https://-doi.org/10.1007/s10013-024-00721-y] on differential stability of parametric optimization…

Optimization and Control · Mathematics 2024-12-17 Nguyen Dong Yen , Duong Thi Viet An , Vu Thi Huong , Nguyen Ngoc Luan

We consider a class of nonsmooth fractional programming problems with fixed-point constraints, where the numerator is convex and the denominator is concave. To solve this problem, we propose splitting algorithms that compute subgradient…

Optimization and Control · Mathematics 2025-09-03 Mootta Prangprakhon , Nimit Nimana

We consider some second order quasilinear partial differential inequalities for real valued functions on the unit ball and find conditions under which there is a lower bound for the supremum of nonnegative solutions that do not vanish at…

Complex Variables · Mathematics 2009-07-21 Adam Coffman , Yifei Pan

In the first part, we discuss the stability of the strong slope and of the subdifferential of a lower semicontinuous function with respect to Wijsman perturbations of the function, i.e. perturbations described via Wijsman convergence. In…

Optimization and Control · Mathematics 2019-01-01 Marc Lassonde

Many problems of theoretical and practical interest involve finding an optimum over a family of convex functions. For instance, finding the projection on the convex functions in $H^k(\Omega)$, and optimizing functionals arising from some…

Numerical Analysis · Mathematics 2008-04-11 Néstor E. Aguilera , Pedro Morin

We present a practical and powerful new framework for both unconstrained and constrained submodular function optimization based on discrete semidifferentials (sub- and super-differentials). The resulting algorithms, which repeatedly compute…

Data Structures and Algorithms · Computer Science 2013-08-13 Rishabh Iyer , Stefanie Jegelka , Jeff Bilmes

We explore the possibility to derive basic calculus rules for some subdifferential constructions associated to set-valued maps between normed vector spaces. Then, we use these results in order to write optimality conditions for a special…

Optimization and Control · Mathematics 2023-11-28 Marius Durea , Elena-Andreea Florea

This paper investigates general and generalized differentiation properties of the optimal value function associated with perturbed optimization problems. Fundamental results on nearly convex sets and functions in infinite-dimensional spaces…

Optimization and Control · Mathematics 2025-10-24 V. S. T. Long , B. S. Mordukhovich , N. M. Nam , L. White

In this paper we study the radial epiderivative notion for nonconvex functions, which extends the (classical) directional derivative concept. The paper presents new definition and new properties for this notion and establishes relationships…

Optimization and Control · Mathematics 2022-09-07 Gulcin Dinc Yalcin , Refail Kasimbeyli

Seminal work by Edmonds and Lovasz shows the strong connection between submodularity and convexity. Submodular functions have tight modular lower bounds, and subdifferentials in a manner akin to convex functions. They also admit poly-time…

Discrete Mathematics · Computer Science 2015-09-09 Rishabh Iyer , Jeff Bilmes

Level proximal subdifferential was introduced by Rockafellar recently for studying proximal mappings of possibly nonconvex functions. In this paper a systematic study of level proximal subdifferential is given. We characterize variational…

Optimization and Control · Mathematics 2026-04-22 Honglin Luo , Xianfu Wang , Ziyuan Wang , Xinmin Yang

In this note, we investigate the supremum and the infimum of the functional $|a_{n+1}|-|a_{n}|$ for functions, convex and analytic on the unit disk, of the form $f(z)=z+a_2z^2+a_3z^3+\dots.$ We also consider the related problem to maximize…

Complex Variables · Mathematics 2016-04-19 Ming Li , Toshiyuki Sugawa

We analyze matrix convex functions of a fixed order defined on a real interval by differential methods as opposed to the characterization in terms of divided differences given by Kraus. We obtain for each order conditions for matrix…

Operator Algebras · Mathematics 2007-05-23 Frank Hansen , Jun Tomiyama

We consider separable nonconvex optimization problems under affine constraints. For these problems, the Shapley-Folkman theorem provides an upper bound on the duality gap as a function of the nonconvexity of the objective functions, but…

Optimization and Control · Mathematics 2025-05-22 Benjamin Dubois-Taine , Alexandre d'Aspremont