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We consider a parabolic equation driven by a nonlinear diffusive operator and we obtain a gradient estimate in the domain where the equation takes place. This estimate depends on the structural constants of the equation, on the geometry of…

Analysis of PDEs · Mathematics 2021-02-08 Serena Dipierro , Zu Gao , Enrico Valdinoci

Stochastic nonconvex optimization problems with nonlinear constraints have a broad range of applications in intelligent transportation, cyber-security, and smart grids. In this paper, first, we propose an inexact-proximal accelerated…

Optimization and Control · Mathematics 2021-07-08 Morteza Boroun , Afrooz Jalilzadeh

In this paper, we derive a priori estimates for the gradient and second order derivatives of solutions to a class of Hessian type fully nonlinear parabolic equations with the first initial-boundary value problem on Riemannian manifolds.…

Analysis of PDEs · Mathematics 2015-02-04 Ge-Jun Bao , Wei-Song Dong

In this paper, we compute universal estimates of eigenvalues for a class of coupled systems of elliptic differential equations in divergence form on a bounded domain in Euclidean space, which includes the well-known Lam\'e and the Laplacian…

Differential Geometry · Mathematics 2026-03-06 Marcio C. Araújo FIlho , Juliana F. R. Miranda , Cristiano S. Silva

We examine gradient descent on unregularized logistic regression problems, with homogeneous linear predictors on linearly separable datasets. We show the predictor converges to the direction of the max-margin (hard margin SVM) solution. The…

Machine Learning · Statistics 2024-10-29 Daniel Soudry , Elad Hoffer , Mor Shpigel Nacson , Suriya Gunasekar , Nathan Srebro

In this work, a novel approach for the solution of the inverse conductivity problem from one and multiple boundary measurements has been developed on the basis of the implication of the framework of BV - functions. The space of the…

Analysis of PDEs · Mathematics 2020-05-20 Antonios Charalambopoulos , Vanessa Markaki , Drosos Kourounis

We investigate a generalization of Calder\'on's problem of recovering the conductivity coefficient in a conductivity equation from boundary measurements. As a model equation we consider the p-conductivity equation with p strictly between…

Analysis of PDEs · Mathematics 2019-01-23 Tommi Brander

This paper investigates a class of non-autonomous highly oscillatory ordinary differential equations characterized by a linear component inversely proportional to a small parameter $\varepsilon$, with purely imaginary eigenvalues, and an…

Numerical Analysis · Mathematics 2026-02-05 Zhihao Qi , Weibing Deng , Fuhai Zhu

The study of first-order optimization is sensitive to the assumptions made on the objective functions. These assumptions induce complexity classes which play a key role in worst-case analysis, including the fundamental concept of algorithm…

Optimization and Control · Mathematics 2024-05-30 Charles Guille-Escuret , Adam Ibrahim , Baptiste Goujaud , Ioannis Mitliagkas

In this paper, which corresponds to an updated version of the author's Habilitation lecture in Mathematics, we do an overview of several topics in elliptic problems. We review some old and new results regarding the Lane-Emden equation, both…

Analysis of PDEs · Mathematics 2024-03-20 Hugo Tavares

This paper deals with nonsmooth convex optimization problems in Euclidean spaces. We identify special elements of the subdifferential of a convex function, called specular gradients. Based on this observation, we propose three numerical…

Optimization and Control · Mathematics 2026-05-26 Kiyuob Jung

We consider gradient descent with constant stepsizes and derive exact worst-case convergence rates on the minimum gradient norm of the iterates. Our analysis covers all possible stepsizes and arbitrary upper/lower bounds on the curvature of…

Optimization and Control · Mathematics 2026-01-23 Teodor Rotaru , François Glineur , Panagiotis Patrinos

We investigate 1) the rate at which refined properties of the empirical risk---in particular, gradients---converge to their population counterparts in standard non-convex learning tasks, and 2) the consequences of this convergence for…

Machine Learning · Computer Science 2018-11-13 Dylan J. Foster , Ayush Sekhari , Karthik Sridharan

The size estimation problem in electrical impedance tomography is considered when the conductivity is a complex number and the body is two-dimensional. Upper and lower bounds on the volume fraction of the unknown inclusion embedded in the…

Analysis of PDEs · Mathematics 2013-10-10 Hyeonbae Kang , Kyoungsun Kim , Hyundae Lee , Xiaofei Li , Graeme W. Milton

In this paper, we provide the universal first-order methods of Composite Optimization with new complexity analysis. It delivers some universal convergence guarantees, which are not linked directly to any parametric problem class. However,…

Optimization and Control · Mathematics 2025-09-26 Yurii Nesterov

In this paper we prove the interior gradient and second derivative estimates for a class of fully nonlinear elliptic equations determined by symmetric functions of eigenvalues of the Ricci or Schouten tensors. As an application we prove the…

Differential Geometry · Mathematics 2007-05-23 Xu-Jia Wang

We consider the inverse conductivity problem of identifying embedded objects in unbounded domains. The main tool is a set of special solutions to the Schroedinger equation, the complex spherical waves, which are constructed by a Carleman…

Analysis of PDEs · Mathematics 2009-11-11 Mikko Salo , Jenn-Nan Wang

In this paper, we study Hessian equations with prescribed contact angle boundary value or oblique derivative boundary value and finally derive the a priori global gradient estimate for the admissible solutions.

Analysis of PDEs · Mathematics 2022-03-08 Peihe Wang

We study inverse boundary problems for the advection diffusion equation on an admissible manifold, i.e. a compact Riemannian manifold with boundary of dimension $\ge 3$, which is conformally embedded in a product of the Euclidean real line…

Analysis of PDEs · Mathematics 2017-04-20 Katya Krupchyk , Gunther Uhlmann

By using local and global versions of Bismut type derivative formulas, gradient estimates are derived for the Neumann semigroup on a narrow strip. Applications to functional/cost inequalities and heat kernel estimates are presented. Since…

Probability · Mathematics 2014-03-18 Feng-Yu Wang