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In this work we analyse the functional ${\cal J}(u)=\|\nabla u\|_\infty$ defined on Lipschitz functions with homogeneous Dirichlet boundary conditions. Our analysis is performed directly on the functional without the need to approximate…

Analysis of PDEs · Mathematics 2020-11-18 Leon Bungert , Yury Korolev , Martin Burger

A generalized variant of the Calder\'on problem from electrical impedance tomography with partial data for anisotropic Lipschitz conductivities is considered in an arbitrary space dimension $n \geq 2$. The following two results are shown:…

Spectral Theory · Mathematics 2012-05-22 Jussi Behrndt , Jonathan Rohleder

We prove a version of the implicit function theorem for Lipschitz mappings $f:\mathbb{R}^{n+m}\supset A \to X$ into arbitrary metric spaces. As long as the pull-back of the Hausdorff content $\mathcal{H}_{\infty}^n$ by $f$ has positive…

Geometric Topology · Mathematics 2019-03-26 Piotr Hajłasz , Scott Zimmerman

Motivated by the rapid rise in statistical tools in Functional Data Analysis, we consider the Gaussian mechanism for achieving differential privacy with parameter estimates taking values in a, potentially infinite-dimensional, separable…

Statistics Theory · Mathematics 2019-01-29 Ardalan Mirshani , Matthew Reimherr , Aleksandra Slavkovic

For utility functions $u$ finite valued on $\mathbb{R}$, we prove a duality formula for utility maximization with random endowment in general semimartingale incomplete markets. The main novelty of the paper is that possibly non locally…

Pricing of Securities · Quantitative Finance 2009-06-02 Sara Biagini , Marco Frittelli , Matheus R. Grasselli

We study Neumann functions for divergence form, second order elliptic systems with bounded measurable coefficients in a bounded Lipschitz domain or a Lipschitz graph domain. We establish existence, uniqueness, and various estimates for the…

Analysis of PDEs · Mathematics 2014-09-25 Jongkeun Choi , Seick Kim

We use porosity to study differentiability of Lipschitz maps on Carnot groups. Our first result states that directional derivatives of a Lipschitz function act linearly outside a $\sigma$-porous set. The second result states that irregular…

Metric Geometry · Mathematics 2016-12-06 Andrea Pinamonti , Gareth Speight

We consider Riemann mappings from bounded Lipschitz domains in the plane to a triangle. We show that in this case the Riemann mapping has a linear variational principle: it is the minimizer of the Dirichlet energy over an appropriate affine…

Computational Geometry · Computer Science 2018-02-13 Nadav Dym , Yaron Lipman , Raz Slutsky

This paper provides a formal econometric framework behind the newly developed difference-in-discontinuities design (DiDC). Despite its increasing use in applied research, there are currently limited studies of its properties. We formalize…

Econometrics · Economics 2026-01-28 Pedro Picchetti , Cristine C. X. Pinto , Stephanie T. Shinoki

This book discusses the interactions between the (nonlinear) metric structure of Banach spaces and their linear asymptotic behavior. The overarching problem is to understand how the various linear structures of a Banach space are preserved…

Functional Analysis · Mathematics 2025-12-02 Florent P. Baudier , Gilles Lancien

In this paper we study the right differentiability of a parametric infimum function over a parametric set defined by equality constraints. We present a new theorem with sufficient conditions for the right differentiability with respect to…

Optimization and Control · Mathematics 2023-06-22 Kevin Sturm

Interatomic potentials are essential to go beyond ab initio size limitations, but simulation results depend sensitively on potential parameters. Forward propagation of parameter variation is key for uncertainty quantification, whilst…

Materials Science · Physics 2024-07-16 Ivan Maliyov , Petr Grigorev , Thomas D Swinburne

We consider the inverse problem of determining the permeability from the pressure in a Darcy model of flow in a porous medium. Mathematically the problem is to find the diffusion coefficient for a linear uniformly elliptic partial…

Statistics Theory · Mathematics 2011-02-02 Masoumeh Dashti , Andrew M. Stuart

Defect of compactness for non-compact imbeddings of Banach spaces can be expressed in the form of a profile decomposition. This paper extends the profile decomposition for Sobolev spaces proved by Solimini (AIHP 1995) to the non-reflexive…

Functional Analysis · Mathematics 2014-09-02 Adimurthi , Cyril Tintarev

It is shown here that if $(Y,\|\cdot\|_Y)$ is a Banach space in which martingale differences are unconditional (a UMD Banach space) then there exists $c=c(Y)\in (0,\infty)$ with the following property. For every $n\in \mathbb{N}$ and…

Functional Analysis · Mathematics 2017-01-18 Tuomas Hytönen , Sean Li , Assaf Naor

We extend a newly developed formal system for the description of astrophysical maps. In this formalism, we consider the difference between maps to be the distance between elements of a pseudometric space (the space of all such maps). This…

Astrophysics · Physics 2009-10-22 Fred C. Adams , Jennifer J. Wiseman

We investigate mapping properties for the Bargmann transform on modulation spaces whose weights and their reciprocals are allowed to grow faster than exponentials. We prove that this transform is isometric and bijective from modulation…

Functional Analysis · Mathematics 2011-06-23 Joachim Toft

This paper develops and implements a nonparametric test of Random Utility Models. The motivating application is to test the null hypothesis that a sample of cross-sectional demand distributions was generated by a population of rational…

Statistics Theory · Mathematics 2018-12-06 Yuichi Kitamura , Jörg Stoye

We establish the Subgradient Theorem for monotone correspondences -- a monotone correspondence is equal to the subdifferential of a potential if and only if it is conservative, i.e. its integral along a closed path vanishes irrespective of…

Theoretical Economics · Economics 2023-08-10 Nicholas C. Bedard , Jacob K. Goeree

We study the problem of efficiently computing the derivative of the fixed-point of a parametric nondifferentiable contraction map. This problem has wide applications in machine learning, including hyperparameter optimization, meta-learning…

Machine Learning · Statistics 2024-06-05 Riccardo Grazzi , Massimiliano Pontil , Saverio Salzo