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The condition number of a differentiable convex function, namely the ratio of its smoothness to strong convexity constants, is closely tied to fundamental properties of the function. In particular, the condition number of a quadratic convex…

Optimization and Control · Mathematics 2020-04-21 David H. Gutman , Javier F. Pena

The error function occurs widely in multiple areas of mathematics, mathematical physics and natural sciences. There has been no work in this area for the past four decades. In this article, we estimate the coefficient bounds with…

Complex Variables · Mathematics 2016-07-08 S. Kanas , C. Ramachandran , L. Vanitha

In this paper, we obtain some new inequalities for functions whose second derivatives' absolute value is s-convex and log-convex. Also, we give some applications for numerical integration.

Classical Analysis and ODEs · Mathematics 2014-09-04 Ahmet Ocak Akdemir , Merve Avci Ardic , M. Emin Özdemir

In \cite{AP2} we obtained general estimates of the operator moduli of continuity of functions on the real line. In this paper we improve the estimates obtained in \cite{AP2} for certain special classes of functions. In particular, we…

Functional Analysis · Mathematics 2011-04-19 Aleksei Aleksandrov , Vladimir Peller

We introduce a notion of a noncommutative function defined on a domain of $d$-tuples of bounded operators on an infinite dimensional Hilbert space. Inverse and implicit function theorems in this setting are established. When these…

Functional Analysis · Mathematics 2021-08-25 Mark E. Mancuso

We quickly review and make some comments on the concept of convexity in metric spaces due to Takahashi. Then we introduce a concept of convex structure based convexity to functions on these spaces and refer to it as $W-$convexity.…

Functional Analysis · Mathematics 2015-09-01 Ahmed A. Abdelhakim

It is demonstrated that multiplier methods naturally yield better constants in strong converse inequalities for the Bernstein-Durrmeyer operator. The absolute constants obtained in some of the inequalities are independent of the weight and…

Classical Analysis and ODEs · Mathematics 2019-09-11 Borislav R. Draganov

We study the relations between some geometric properties of maximal monotone operators and generic geometric and analytical properties of the functions on the associate Fitzpatrick family of convex representations. We also investigate under…

Functional Analysis · Mathematics 2012-07-13 B. F. Svaiter

The dominant method for defining multivariate operator means is to express them as fix-points under a contraction with respect to the Thompson metric. Although this method is powerful, it crucially depends on monotonicity. We are developing…

Mathematical Physics · Physics 2018-12-21 Frank Hansen

In this paper, some Jensen's type inequalities between quaternionic bounded selfadjoint operators on quaternionic Hilbert spaces are proved, using a log-convex function. Also, by applying a specific log-convex function, some particular…

Functional Analysis · Mathematics 2025-04-17 Massoumeh Fashandi

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

Let f be a non-negative concave function on the positive half-line. Let A and B be two positive matrices. Then, for all symmetric norms, || f(A+B) || is less than || f(A)+f(B) ||. When f is operator concave, this was proved by Ando and…

Functional Analysis · Mathematics 2007-05-23 Jean-Christophe Bourin , Mitsuru Uchiyama

This study focuses on convex functions and their generalized. Thus, we start this study by giving the definition of convex functions and some of their properties and discussing a simple geometric property. Then we generalize E-convex…

Classical Analysis and ODEs · Mathematics 2017-04-27 Adem Kilicman , Wedad Saleh

We study the manner in which a sequence of spectral shift functions $\xi(\cdot;H_j,H_{0,j})$ associated with abstract pairs of self-adjoint operators $(H_j, H_{0,j})$ in Hilbert spaces $\cH_j$, $j\in\bbN$, converge to a limiting spectral…

Spectral Theory · Mathematics 2011-11-02 Fritz Gesztesy , Roger Nichols

The article is devoted to the development of numerical methods for solving saddle point problems and variational inequalities with simplified requirements for the smoothness conditions of functionals. Recently there were proposed some…

Optimization and Control · Mathematics 2023-11-22 Alexander Titov , Fedor Stonyakin , Mohammad Alkousa , Alexander Gasnikov

We consider minimization of stochastic functionals that are compositions of a (potentially) non-smooth convex function $h$ and smooth function $c$ and, more generally, stochastic weakly-convex functionals. We develop a family of stochastic…

Optimization and Control · Mathematics 2018-09-25 John Duchi , Feng Ruan

In this paper, we present some operator and eigenvalue inequalities involving operator monotone, doubly concave and doubly convex functions. These inequalities provide some variants of operator Acz\'{e}l inequality and its reverse via…

Functional Analysis · Mathematics 2020-01-16 Shigeru Furuichi , Mohammad Reza Jabbarzadeh , Venus Kaleibary

We characterize real functions $f$ on an interval $(-\alpha,\alpha)$ for which the entrywise matrix function $[a_{ij}] \mapsto [f(a_{ij})]$ is positive, monotone and convex, respectively, in the positive semidefiniteness order. Fractional…

Functional Analysis · Mathematics 2007-10-09 Fumio Hiai

We use the relative modular operator to define a generalized relative entropy for any convex operator function g on the positive real line satisfying g(1) = 0. We show that these convex operator functions can be partitioned into convex…

Mathematical Physics · Physics 2015-06-26 Andrew Lesniewski , Mary Beth Ruskai

We connect high-dimensional subset selection and submodular maximization. Our results extend the work of Das and Kempe (2011) from the setting of linear regression to arbitrary objective functions. For greedy feature selection, this…

Machine Learning · Statistics 2017-10-13 Ethan R. Elenberg , Rajiv Khanna , Alexandros G. Dimakis , Sahand Negahban