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Convex optimization is a vibrant and successful area due to the existence of a variety of efficient algorithms that leverage the rich structure provided by convexity. Convexity of a smooth set or a function in a Euclidean space is defined…

最优化与控制 · 数学 2018-06-19 Nisheeth K. Vishnoi

This paper studies the convexity properties of nonsmooth extended-real-valued weakly convex functions, a class of functions that is central to modern optimization and its applications. We establish new characterizations of convexity using…

最优化与控制 · 数学 2026-03-27 Vo Thanh Phat

We study the geodesic convexity of various energy and entropy functionals restricted to (non-geodesically convex) submanifolds of Wasserstein spaces with their induced geometry. We prove a variety of convexity results by means of a simple…

偏微分方程分析 · 数学 2025-08-22 Louis-Pierre Chaintron , Daniel Lacker

We introduce Wasserstein-like dynamical transport distances between vector-valued densities on the real line. The mobility function from the scalar theory is replaced by a mobility matrix, that is subject to positivity and concavity…

偏微分方程分析 · 数学 2016-01-18 Jonathan Zinsl , Daniel Matthes

This paper presents necessary, sufficient, and equivalent conditions for the spherical convexity of non-homogeneous quadratic functions. In addition to motivating this study and identifying useful criteria for determining whether such…

最优化与控制 · 数学 2025-02-12 R. Bolton , S. Z. Németh

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…

最优化与控制 · 数学 2015-07-21 Boris S. Mordukhovich , M. Ebrahim Sarabi

It is well known that nonlinear diffusion equations can be interpreted as a gradient flow in the space of probability measures equipped with the Euclidean Wasserstein distance. Under suitable convexity conditions on the nonlinearity, due to…

偏微分方程分析 · 数学 2014-02-13 François Bolley , José A. Carrillo

A curve is rectifying if it lies on a moving hyperplane orthogonal to its curvature vector. In this work, we extend the main result of [Chen 2017, Tamkang J. Math. 48, 209] to any space dimension: we prove that rectifying curves are…

微分几何 · 数学 2022-09-22 Luiz C. B. da Silva , Gilson S. Ferreira

The geodesic deviation equation (GDE) describes the tendency of objects to accelerate towards or away from each other due to spacetime curvature. The GDE assumes that nearby geodesics have a small rate of separation, which is formally…

广义相对论与量子宇宙学 · 物理学 2022-06-28 Isaac Raj Waldstein , J. David Brown

We present a brief but nearly self-contained proof of a formula for the Weil-Petersson Hessian of the geodesic length of a closed curve (either simple or not simple) on a hyperbolic surface. The formula is the sum of the integrals of two…

微分几何 · 数学 2009-02-03 Michael Wolf

The Hessian of a differentiable convex function is positive semidefinite. Therefore, checking the Hessian of a given function is a natural approach to certify convexity. However, implementing this approach is not straightforward since it…

最优化与控制 · 数学 2022-10-20 Julien Klaus , Niklas Merk , Konstantin Wiedom , Sören Laue , Joachim Giesen

Differentiable structure ensures that many of the basics of classical convex analysis extend naturally from Euclidean space to Riemannian manifolds. Without such structure, however, extensions are more challenging. Nonetheless, in…

最优化与控制 · 数学 2023-11-28 Adrian S. Lewis , Genaro López-Acedo , Adriana Nicolae

We derive estimates of the Hessian of two smooth functions defined on Grassmannian manifold. Based on it, we can derive curvature estimates for minimal submanifolds in Euclidean space via Gauss map. In this way, the result for Bernstein…

微分几何 · 数学 2008-06-27 Y. L. Xin , Ling Yang

We study fully nonlinear geometric flows that deform strictly $k$-convex hypersurfaces in Euclidean space with pointwise normal speed given by a concave function of the principal curvatures. Specifically, the speeds we consider are obtained…

微分几何 · 数学 2020-07-16 Stephen Lynch

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…

经典分析与常微分方程 · 数学 2017-04-27 Adem Kilicman , Wedad Saleh

We present a strikingly simple proof that two rules are sufficient to automate gradient descent: 1) don't increase the stepsize too fast and 2) don't overstep the local curvature. No need for functional values, no line search, no…

最优化与控制 · 数学 2020-08-18 Yura Malitsky , Konstantin Mishchenko

A notion of differentiability is being proposed for maps between Wasserstein spaces of order 2 of smooth, connected and complete Riemannian manifolds. Due to the nature of the tangent space construction on Wasserstein spaces, we only give a…

度量几何 · 数学 2020-10-06 Bernadette Lessel , Thomas Schick

In this paper, we study higher-order-accurate-in-time minimizing movements schemes for Wasserstein gradient flows. We introduce a novel accelerated second-order scheme, leveraging the differential structure of the Wasserstein space in both…

偏微分方程分析 · 数学 2025-12-23 Raymond Chu , Matt Jacobs

A characterization of the proximal normal cone is obtained and a separation theorem for convex subsets of Riemannian manifolds is established. Moreover, the convexity of the distance function $d_S$ for a convex subset $S$ in the cases where…

微分几何 · 数学 2018-05-08 S. Khajehpour , M. R. Pouryayevali

We consider a smooth Euclidean solid cone endowed with a smooth homogeneous density function used to weight Euclidean volume and hypersurface area. By assuming convexity of the cone and a curvature-dimension condition we prove that the…

微分几何 · 数学 2013-04-17 Antonio Cañete , César Rosales
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