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Given a linear control system in a Hilbert space with a bounded control operator, we establish a characterization of exponential stabilizability in terms of an observability inequality. Such dual characterizations are well known for exact…

Optimization and Control · Mathematics 2019-11-13 Emmanuel Trélat , Gengsheng Wang , Yashan Xu

Young's inequality is extended to the context of absolutely continuous measures. Several applications are included.

Classical Analysis and ODEs · Mathematics 2011-09-28 Flavia Corina Mitroi , Constantin P. Niculescu

The Friedland-Hayman inequality is a sharp inequality concerning the growth rates of homogeneous, harmonic functions with Dirichlet boundary conditions on complementary cones dividing Euclidean space into two parts. In this paper, we prove…

Analysis of PDEs · Mathematics 2024-06-19 Thomas Beck , David Jerison

We establish the existence of extremizers for a Fourier restriction inequality on planar convex arcs without points with colinear tangents whose curvature satisfies a natural assumption. More generally, we prove that any extremizing…

Classical Analysis and ODEs · Mathematics 2012-10-03 Diogo Oliveira e Silva

In this paper we present several applications of Cartwright-Field's inequality. Among these we found Young's inequality, Bernoulli's inequality, the inequality between the weighted power means, H\"{o}lder's inequality and Cauchy's…

Classical Analysis and ODEs · Mathematics 2011-03-21 Nicuşor Minculete , Shigeru Furuichi

In what follows we improve an inequality related to matrix theory. T. Laffey proved (2013) a weaker form of this inequality [2].

General Mathematics · Mathematics 2016-05-20 Dov Aharonov

We establish two inequalities in real inner product spaces. The first is a multiplicative strengthening of the classical Hornich-Hlawka inequality: for all vectors $x, y, z$ in a real inner product space $H$ \[ \|x\|\,\|y\| +…

Classical Analysis and ODEs · Mathematics 2026-05-12 Nizar El Idrissi , Hicham Zoubeir

In this paper, we obtain some new estimations of Iyengar-type inequality in which quasi-convex(quasi-concave) functions are involved. These estimations are improvements of some recently obtained estimations. Some error estimations for the…

Functional Analysis · Mathematics 2012-09-13 M. Emin Ozdemir

Motivated by the direct method in the calculus of variations in $L^{\infty}$, our main result identifies the notion of convexity characterizing the weakly$^*$ lower semicontinuity of nonlocal supremal functionals: Cartesian level convexity.…

Analysis of PDEs · Mathematics 2022-04-18 Carolin Kreisbeck , Antonella Ritorto , Elvira Zappale

We prove a sharp analog of Young's inequality on $S^N$, and deduce from it certain sharp entropy inequalities. The proof turns on constructing a nonlinear heat flow that drives trial functions to optimizers in a monotonic manner. This…

Functional Analysis · Mathematics 2007-05-23 Eric Carlen , Elliott Lieb , Michael Loss

We explicitly solve a variational problem related to upper bounds on the optimal constants in the Cwikel--Lieb--Rozenblum (CLR) and Lieb--Thirring (LT) inequalities, which has recently been derived in [Invent. Math. 231 (2023), no.1,…

Mathematical Physics · Physics 2025-03-24 Thiago Carvalho Corso , Tobias Ried

As an alternative to the well-known methods of "chaining" and "bracketing" that have been developed in the study of random fields, a new method, which is based on a stochastic maximal inequality derived by using the Taylor expansion, is…

Probability · Mathematics 2020-08-03 Yoichi Nishiyama

The original motivation for this paper was to provide an efficient quantitative analysis of convex infinite (or semi-infinite) inequality systems whose decision variables run over general infinite-dimensional (resp. finite-dimensional)…

Optimization and Control · Mathematics 2011-02-11 M. J. Cánovas , M. A. LóPez , B. S. Mordukhovich , J. Parra

In this article, we provide a novel and broadly-applicable contraction-theoretic approach to continuous-time time-varying convex optimization. For any parameter-dependent contracting dynamics, we show that the tracking error is…

Optimization and Control · Mathematics 2025-07-24 Alexander Davydov , Veronica Centorrino , Anand Gokhale , Giovanni Russo , Francesco Bullo

We analyze the role played by $n$-convexity for the fulfillment of a series of linear functional inequalities that extend the Hornich-Hlawka functional inequality, $f\left( x\right) +f\left( y\right) +f\left( z\right) +f\left( x+y+z\right)…

Functional Analysis · Mathematics 2023-01-23 Constantin P. Niculescu , Suvrit Sra

The objective quantification of similarity between two mathematical structures constitutes a recurrent issue in science and technology. In the present work, we developed a principled approach that took the Kronecker's delta function of two…

Machine Learning · Computer Science 2021-11-05 Luciano da F. Costa

The main purpose of this paper is to prove a sharp Sobolev inequality in an exterior of a convex bounded domain. There are two ingredients in the proof: One is the observation of some new isoperimetric inequalities with partial free…

Analysis of PDEs · Mathematics 2007-05-23 Meijun Zhu

Submodular continuous functions are a category of (generally) non-convex/non-concave functions with a wide spectrum of applications. We characterize these functions and demonstrate that they can be maximized efficiently with approximation…

Machine Learning · Computer Science 2019-05-07 Andrew An Bian , Baharan Mirzasoleiman , Joachim M. Buhmann , Andreas Krause

The inverse tangent function can be bounded by different inequalities, for example by Shafer's inequality. In this publication, we propose a new sharp double inequality, consisting of a lower and an upper bound, for the inverse tangent…

Information Theory · Computer Science 2013-07-19 Gholamreza Alirezaei

From a variational perspective, many statistical learning criteria involve seeking a distribution that balances empirical risk and regularization. In this paper, we broaden this perspective by introducing a new general class of variational…

Machine Learning · Computer Science 2026-02-17 Sophia Sklaviadis , Thomas Moellenhoff , Andre Martins , Mario Figueiredo
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