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A fundamental open question asking whether all real-valued strongly quasiconvex functions defined on $\mathbb R^n$ are necessarily continuous, akin to their convex counterparts, is answered in detail in this paper. Among other things, we…

Optimization and Control · Mathematics 2025-12-04 Nguyen Thi Van Hang , Felipe Lara , Nguyen Dong Yen

A class of real functions, which is the generalization of a family of convex functions, is introduced; in this connection, we have defined $X$-convex, strictly $X$-convex, quasi-$X$-convex, strictly quasi-$X$-convex, and semi-strictly…

Optimization and Control · Mathematics 2022-08-16 Musavvir Ali , Ehtesham Akhter

For a $\mathcal{C}^2$-smooth function on a finite-dimensional space, a necessary condition for its quasiconvexity is the positive semidefiniteness of its Hessian matrix on the subspace orthogonal to its gradient, whereas a sufficient…

Functional Analysis · Mathematics 2018-10-31 Pham Duy Khanh , Vo Thanh Phat

Let $E$ be a real vector space with dual space $E^*$ and let $C\subset E$ be a convex subset with more than one point. Let $f : C\to\mathbb{R}$ be a function satisfying a mild stability property at 'flat' points of the (relative) boundary…

Optimization and Control · Mathematics 2015-04-21 Khanh Pham Duy , Marc Lassonde

Many problems of theoretical and practical interest involve finding a convex or concave function. For instance, optimization problems such as finding the projection on the convex functions in $H^k(\Omega)$, or some problems in economics. In…

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

We present an example of smooth quasi-convex functions in the positive octant of $\mathbb{R}^{3}$ which cannot be obtained as the images of convex smooth functions under a monotone smooth mappings of $\mathbb{R}$.

Optimization and Control · Mathematics 2017-11-21 N. V. Krylov

We consider the space of convex functions defined in the Euclidean $n$-dimensional space, which are lower semi-continuous and tend to infinity at infinity. We study real-valued valuations defined on this space of functions, which are…

Metric Geometry · Mathematics 2015-08-04 L. Cavallina , A. Colesanti

In this article we utilise abstract convexity theory in order to unify and generalize many different concepts from nonsmooth analysis. We introduce the concepts of abstract codifferentiability, abstract quasidifferentiability and abstract…

Optimization and Control · Mathematics 2018-10-03 M. V. Dolgopolik

This paper concerns matrix "convex" functions of (free) noncommuting variables, $x = (x_1, \ldots, x_g)$. Helton and McCullough showed that a polynomial in $x$ which is matrix convex is of degree two or less. We prove a more general result:…

Functional Analysis · Mathematics 2015-01-27 J. William Helton , J. E. Pascoe , Ryan Tully-Doyle , Victor Vinnikov

Convexity plays a prominent role in a number of problems, but practical considerations frequently give rise to non-convex functions. We suggest a method for determining convex regions, and also for assessing the lack of convexity in the…

Functional Analysis · Mathematics 2018-08-20 Youri Davydov , Elina Moldavskaya , Ričardas Zitikis

We introduce and study a new class of generalized convex functions termed star quasiconvex functions. This class includes convex, star-convex, quasiconvex, quasar-convex, and positively homogeneous functions of any degree $p>0$ as special…

Optimization and Control · Mathematics 2026-05-27 Phan Quoc Khanh , Felipe Lara

We give three proofs of the fact that a smoothly bounded, convex domain in R^n has smooth defining functions whose Hessians are non-negative definite in a neighborhood of the boundary of the domain.

Complex Variables · Mathematics 2012-04-04 A. -K. Herbig , J. D. McNeal

In this paper, we discuss the problem of minimizing the sum of two convex functions: a smooth function plus a non-smooth function. Further, the smooth part can be expressed by the average of a large number of smooth component functions, and…

Machine Learning · Computer Science 2016-11-17 Luo Luo , Zihao Chen , Zhihua Zhang , Wu-Jun Li

Nearly convex sets play important roles in convex analysis, optimization and theory of monotone operators. We give a systematic study of nearly convex sets, and construct examples of subdifferentials of lower semicontinuous convex functions…

Optimization and Control · Mathematics 2015-07-28 Sarah M. Moffat , Walaa M. Moursi , Xianfu Wang

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

Let $\Delta_m$ be the standard $m$-dimensional simplex of non-negative $m+1$ tuples that sum to unity and let $S$ be a nonempty subset of $\Delta_m$. A real valued function $h$ defined on a convex subset of a real vector space is $S$-almost…

Functional Analysis · Mathematics 2007-05-23 S. J. Dilworth , Ralph Howard , James W. Roberts

Two criteria for the robust quasiconvexity of lower semicontinuous functions are established in terms of Fr\'echet subdifferentials in Asplund spaces.

Functional Analysis · Mathematics 2018-04-20 Hoa T. Bui , Pham Duy Khanh , Tran Thi Tu Trinh

Subdifferentials (in the sense of convex analysis) of matrix-valued functions defined on $\mathbb{R}^d$ that are convex with respect to the L\"{o}wner partial order can have a complicated structure and might be very difficult to compute…

Optimization and Control · Mathematics 2024-07-22 M. V. Dolgopolik

The paper is devoted to a comprehensive second-order study of a remarkable class of convex extended-real-valued functions that is highly important in many aspects of nonlinear and variational analysis, specifically those related to…

Optimization and Control · Mathematics 2015-07-21 Boris S. Mordukhovich , M. Ebrahim Sarabi

Functions with uniform level sets can represent orders, preference relations or other binary relations and thus turn out to be a tool for scalarization that can be used, e.g., in multicriteria optimization, decision theory, mathematical…

Optimization and Control · Mathematics 2016-08-11 Petra Weidner
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