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We get a new multiplicity result for gradient systems. Here is a very particular corollary: Let $\Omega\subset {\bf R}^n$ ($n\geq 2$) be a smooth bounded domain and let $\Phi:{\bf R}^2\to {\bf R}$ be a $C^1$ function, with $\Phi(0,0)=0$,…

Analysis of PDEs · Mathematics 2021-03-16 Biagio Ricceri

Non-smoothness at optimal points is a common phenomenon in many eigenvalue optimization problems. We consider two recent algorithms to minimize the largest eigenvalue of a Hermitian matrix dependent on one parameter, both proven to be…

Numerical Analysis · Mathematics 2018-05-14 Fatih Kangal , Emre Mengi

This paper studies estimation of a smooth function $f(t,s)$ when we are given functional responses of the form $f(t,\cdot)$ + error, but scientific interest centers on the collection of functions $f(\cdot,s)$ for different $s$. The…

Methodology · Statistics 2014-12-03 Philip T. Reiss , Lei Huang , Huaihou Chen , Stan Colcombe

In the article the authors consider the class ${\mathcal H}_0$ of sense-preserving harmonic functions $f=h+\overline{g}$ defined in the unit disk $|z|<1$ and normalized so that $h(0)=0=h'(0)-1$ and $g(0)=0=g'(0)$, where $h$ and $g$ are…

Complex Variables · Mathematics 2015-06-02 Liulan Li , Saminathan Ponnusamy

This paper studies non-smooth problems of convex stochastic optimization. Using the smoothing technique based on the replacement of the function value at the considered point by the averaged function value over a ball (in $l_1$-norm or…

Optimization and Control · Mathematics 2023-05-23 Aleksandr Lobanov , Belal Alashqar , Darina Dvinskikh , Alexander Gasnikov

Let $N$ be a finite set of cardinality $n$, and $a\in N$. A submodular function $f$ on $N$ with $f(a)=1$ is defined to be $a$-reduced if, for any decomposition $f=g+h$ into submodular functions where $h$ does not depend on $a$, it follows…

Combinatorics · Mathematics 2026-04-28 Laszlo Csirmaz

We give a new characterization of a continuous embedding between two function spaces of type $G\Gamma$. Such spaces are governed by functionals of type \begin{equation*} \|f\|_{G\Gamma(r,q;w,\delta)} := \left(\int_{0}^{L} \left(…

Functional Analysis · Mathematics 2026-03-05 Amiran Gogatishvili , Zdeněk Mihula , Luboš Pick , Hana Turčinová , Tuğçe Ünver

In this work, a convergence lemma for function $f$ being finite compositions of analytic mappings and the maximum operator is proved. The lemma shows that the set of $\delta$-stationary points near an isolated local minimum point $x^*$ is…

Computer Science and Game Theory · Computer Science 2022-08-12 Xiaotie Deng , Hanyu Li , Ningyuan Li

Let $\Delta_x f(x,y)=f(x+1,y)-f(x,y)$ and $\Delta_y f(x,y)=f(x,y+1)-f(x,y)$ be the difference operators with respect to $x$ and $y$. A rational function $f(x,y)$ is called summable if there exist rational functions $g(x,y)$ and $h(x,y)$…

Symbolic Computation · Computer Science 2014-08-12 Qing-Hu Hou , Rong-Hua Wang

Let $A$ and $ B$ be $n\times n$ positive definite complex matrices, let $\sigma$ be a matrix mean, and let $f : [0,\infty)\to [0,\infty)$ be a differentiable convex function with $f(0)=0$. We prove that $$f^{\prime}(0)(A \sigma B)\leq…

Functional Analysis · Mathematics 2024-04-19 Manisha Devi , Jaspal Singh Aujla , Mohsen Kian , Mohammad Sal Moslehian

We consider optimizing a function smooth convex function $f$ that is the average of a set of differentiable functions $f_i$, under the assumption considered by Solodov [1998] and Tseng [1998] that the norm of each gradient $f_i'$ is bounded…

Optimization and Control · Mathematics 2013-08-30 Mark Schmidt , Nicolas Le Roux

Probabilistic smoothing is a standard tool for global optimization, but existing methods rely on Gaussian kernels and specific transforms, often resulting in strong hyperparameter sensitivity and limited robustness. We propose a general…

Machine Learning · Computer Science 2026-05-27 Kukyoung Jang , Taehyun Cho , Junrui Zhang , Ping Xu , Kyungjae Lee

Consider an open set $\mathbb{D}\subseteq\mathbb{R}^n$, equipped with a probability measure $\mu$. An important characteristic of a smooth function $f:\mathbb{D}\rightarrow\mathbb{R}$ is its \emph{second-moment matrix} $\Sigma_{\mu}:=\int…

Information Theory · Computer Science 2019-09-10 Armin Eftekhari , Michael B. Wakin , Ping Li , Paul G. Constantine

Symmetric submodular functions are an important family of submodular functions capturing many interesting cases including cut functions of graphs and hypergraphs. Maximization of such functions subject to various constraints receives little…

Data Structures and Algorithms · Computer Science 2016-04-19 Moran Feldman

We consider several classes of highly important semidefinite optimization problems that involve both a convex objective function (smooth or nonsmooth) and additional linear or nonlinear smooth and convex constraints, which are ubiquitous in…

Optimization and Control · Mathematics 2025-04-08 Dan Garber , Atara Kaplan

We study the min-max optimization problem where each function contributing to the max operation is strongly-convex and smooth with bounded gradient in the search domain. By smoothing the max operator, we show the ability to achieve an…

Optimization and Control · Mathematics 2019-05-31 Hakan Gokcesu , Kaan Gokcesu , Suleyman Serdar Kozat

We study the problem of finding a function u verifying --$\Delta$u = 0 in $\Omega$ under the boundary condition $\partial$u $\partial$n + g(u) = $\mu$ on $\partial$$\Omega$ where $\Omega$ $\subset$ R N is a smooth domain, n the normal unit…

Analysis of PDEs · Mathematics 2020-03-03 Oussama Boukarabila , Laurent Veron

We show that there are functions $f$ in the H\"older class $C^{ { \alpha }}[0,1]$, $1< { \alpha }<2$ such that $f|_{A}$ is not convex, nor concave for any $A { \subset } [0,1]$ with $ { \bar { dim }_M } A> { \alpha }-1$. Our earlier result…

Classical Analysis and ODEs · Mathematics 2017-02-06 Zoltan Buczolich

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

This paper considers the minimization of a general objective function $f(X)$ over the set of rectangular $n\times m$ matrices that have rank at most $r$. To reduce the computational burden, we factorize the variable $X$ into a product of…

Information Theory · Computer Science 2018-07-04 Zhihui Zhu , Qiuwei Li , Gongguo Tang , Michael B. Wakin
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