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In this paper, we obtain coefficient criteria for a normalized harmonic function defined in the unit disk to be close-to-convex and fully starlike, respectively. Using these coefficient conditions, we present different classes of harmonic…

Complex Variables · Mathematics 2012-06-05 S. V. Bharanedhar , S. Ponnusamy

This paper explores some connections between rank one convexity, multiplicative quasiconvexity and Schur convexity. Theorem 5.1 gives simple necessary and sufficient conditions for an isotropic objective function to be rank one convex on…

Functional Analysis · Mathematics 2009-11-15 Marius Buliga

Smoothed analysis of complexity bounds and condition numbers has been done, so far, on a case by case basis. In this paper we consider a reasonably large class of condition numbers for problems over the complex numbers and we obtain…

Numerical Analysis · Mathematics 2007-05-23 Peter Buergisser , Felipe Cucker , Martin Lotz

This paper studies the strong quasiconvexity of norm and distance functions in finite-dimensional normed spaces. Although the Euclidean norm is known to be strongly quasiconvex on bounded convex sets, a complete characterization of this…

Optimization and Control · Mathematics 2026-05-26 V. S. T. Long , N. M. Nam

In the article the necessary and sufficient conditions for a representation of Lipschitz function of more than two variables as a difference of two convex functions are formulated. An algorithm of this representation is given. The outcome…

Functional Analysis · Mathematics 2017-09-12 Igor Proudnikov

Several results on constrained spline smoothing are obtained. In particular, we establish a general result, showing how one can constructively smooth any monotone or convex piecewise polynomial function (ppf) (or any $q$-monotone ppf,…

Numerical Analysis · Mathematics 2014-04-01 K. Kopotun , D. Leviatan , A. Prymak

Composite optimization problems, where the sum of a smooth and a merely lower semicontinuous function has to be minimized, are often tackled numerically by means of proximal gradient methods as soon as the lower semicontinuous part of the…

Optimization and Control · Mathematics 2022-07-05 Christian Kanzow , Patrick Mehlitz

This paper deals with convex nonsmooth optimization problems. We introduce a general smooth approximation framework for the original function and apply random (accelerated) coordinate descent methods for minimizing the corresponding smooth…

Optimization and Control · Mathematics 2024-01-10 Flavia Chorobura , Ion Necoara

We provide some conditions for the graph of a Hoelder-continuous function on \bar{D}, where \bar{D} is a closed disc in the complex plane, to be polynomially convex. Almost all sufficient conditions known to date --- provided the function…

Complex Variables · Mathematics 2015-08-28 Gautam Bharali

We show that $C^0$-fine approximation of convex functions by smooth (or real analytic) convex functions on $\R^d$ is possible in general if and only if $d=1$. Nevertheless, for $d\geq 2$ we give a characterization of the class of convex…

Classical Analysis and ODEs · Mathematics 2012-01-24 Daniel Azagra

In Learning Theory, the smoothness assumption on the target function (known as source condition) is a key factor in establishing theoretical convergence rates for an estimator. The existing general form of the source condition, as discussed…

Statistics Theory · Mathematics 2025-03-27 Naveen Gupta , S. Sivananthan

We introduce and investigate a new generalized convexity notion for functions called prox-convexity. The proximity operator of such a function is single-valued and firmly nonexpansive. We provide examples of (strongly) quasiconvex, weakly…

Optimization and Control · Mathematics 2021-11-30 Sorin-Mihai Grad , Felipe Lara

We derive bounds relating Renegar's condition number to quantities that govern the statistical performance of convex regularization in settings that include the $\ell_1$-analysis setting. Using results from conic integral geometry, we show…

Numerical Analysis · Mathematics 2019-09-30 Dennis Amelunxen , Martin Lotz , Jake Walvin

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

In this paper we show how the superquadratic functions can be used as a tool for researching other types of convex functions like $\phi $-convexity, strong-convexity and uniform convexity. We show how to use inequalities satisfied by…

Functional Analysis · Mathematics 2024-08-15 Shoshana Abramovich

In the high-dimensional data setting, the sample covariance matrix is singular. In order to get a numerically stable and positive definite modification of the sample covariance matrix in the high-dimensional data setting, in this paper we…

Numerical Analysis · Mathematics 2021-01-20 Shaoxin Wang

Based on the characterization of the polyconvex envelope of isotropic functions by their signed singular value representations, we propose a simple algorithm for the numerical approximation of the polyconvex envelope. Instead of operating…

Numerical Analysis · Mathematics 2023-07-31 Timo Neumeier , Malte A. Peter , Daniel Peterseim , David Wiedemann

In this paper we build the relationship between smoothness of the functions and convergence rate along curves for a class of generalized Schr\"{o}dinger operators with polynomial growth. We show that the convergence rate depends only on the…

Classical Analysis and ODEs · Mathematics 2021-08-31 Wenjuan Li , Huiju Wang

Let us say that a convex function f\colon C\to[-\infty,\infty] on a convex set C\subseteq\R is infimum-stable if, for any sequence (f_n) of convex functions f_n\colon C\to[-\infty,\infty] converging to f pointwise, one has \inf_C…

Optimization and Control · Mathematics 2013-08-05 Iosif Pinelis

In this paper we consider a composite optimization problem that minimizes the sum of a weakly smooth function and a convex function with either a bounded domain or a uniformly convex structure. In particular, we first present a…

Optimization and Control · Mathematics 2023-05-30 Masaru Ito , Zhaosong Lu , Chuan He