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Related papers: Resolvent metrics and heat kernel estimates

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We solve the metrisability problem for generic three-dimensional projective structures.

Differential Geometry · Mathematics 2018-01-18 Michael Eastwood

We introduce higher-order Stein kernels relative to the standard Gaussian measure, which generalize the usual Stein kernels by involving higher-order derivatives of test functions. We relate the associated discrepancies to various metrics…

Probability · Mathematics 2018-12-07 Max Fathi

The problem of resolving the fine details of a signal from its coarse scale measurements or, as it is commonly referred to in the literature, the super-resolution problem arises naturally in engineering and physics in a variety of settings.…

Information Theory · Computer Science 2015-04-14 Tamir Bendory , Shai Dekel , Arie Feuer

Classical and nonclassical symmetries of the nonlinear heat equation $$u_t=u_{xx}+f(u),\eqno(1)$$ are considered. The method of differential Gr\"obner bases is used both to find the conditions on $f(u)$ under which symmetries other than the…

solv-int · Physics 2008-02-03 Peter A. Clarkson , Elizabeth L. Mansfield

In this article, we consider the problem of estimating the heat kernel on measure-metric spaces equipped with a resistance form. Such spaces admit a corresponding resistance metric that reflects the conductivity properties of the set. In…

Probability · Mathematics 2012-10-23 David A. Croydon

This document provides a brief overview of different metrics and terminology that is used to measure the performance of binary classification systems.

Machine Learning · Computer Science 2014-10-21 Sebastian Raschka

We generalize Killing equations to a test particle system which is subjected to external force. We relax the conservation condition by virtue of reparametrization invariance of a particle orbit. As a result, we obtain generalized Killing…

General Relativity and Quantum Cosmology · Physics 2010-03-04 Takahisa Igata , Tatsuhiko Koike , Hideki Ishihara

Indefinite Kaehler solutions of the Einstein equations are studied, and it is almost completely determined which compact complex surfaces admit such metrics.

dg-ga · Mathematics 2009-10-28 Jimmy Petean

The goal in thinning is to summarize a dataset using a small set of representative points. Remarkably, sub-Gaussian thinning algorithms like Kernel Halving and Compress can match the quality of uniform subsampling while substantially…

Machine Learning · Statistics 2026-03-03 Annabelle Michael Carrell , Albert Gong , Abhishek Shetty , Raaz Dwivedi , Lester Mackey

This paper proposes new algorithms for the metric learning problem. We start by noticing that several classical metric learning formulations from the literature can be viewed as modified covariance matrix estimation problems. Leveraging…

Machine Learning · Statistics 2022-11-23 Antoine Collas , Arnaud Breloy , Guillaume Ginolhac , Chengfang Ren , Jean-Philippe Ovarlez

This paper presents a novel feature of the kernel-based system identification method. We prove that the regularized kernel-based approach for the estimation of a finite impulse response is equivalent to a robust least-squares problem with a…

Optimization and Control · Mathematics 2021-05-27 Mohammad Khosravi , Roy S. Smith

A survey of problems, conjectures, and theorems about quasi-isometric classification and rigidity for finitely generated solvable groups.

Group Theory · Mathematics 2007-05-23 Benson Farb , Lee Mosher

We define measures on central extension of current groups in any dimension by using infinite dimensional Brownian motion.

Probability · Mathematics 2008-04-24 Remi Leandre

In his celebrated article, Aronson established Gaussian bounds for the fundamental solution to the Cauchy problem governed by a second order divergence form operator with uniformly elliptic coefficients. We extend Aronson's proof of upper…

Analysis of PDEs · Mathematics 2021-11-15 Moritz Kassmann , Marvin Weidner

The present paper proposes generalized Gaussian kernel adaptive filtering, where the kernel parameters are adaptive and data-driven. The Gaussian kernel is parametrized by a center vector and a symmetric positive definite (SPD) precision…

Machine Learning · Computer Science 2021-05-20 Tomoya Wada , Kosuke Fukumori , Toshihisa Tanaka , Simone Fiori

This paper is an exposition of several questions linking heat kernel measures on infinite dimensional Lie groups, limits associated with critical Sobolev exponents, and Feynmann-Kac measures for sigma models.

Functional Analysis · Mathematics 2007-11-06 Doug Pickrell

We study the gradient regularity of solutions to measure data elliptic systems with Uhlenbeck-type structure and Orlicz growth. For any bounded Borel measure, pointwise estimates for the gradient of solutions are provided in terms of the…

Analysis of PDEs · Mathematics 2023-07-31 Iwona Chlebicka , Minhyun Kim , Marvin Weidner

A robust mean value is often a good alternative to the standard mean value when dealing with data containing many outliers. An efficient method for samples of one-dimensional features and the truncated quadratic error norm is presented and…

Computer Vision and Pattern Recognition · Computer Science 2016-02-01 Erik Jonsson , Michael Felsberg

Resilient systems are able to recover quickly and easily from disturbed system states that might result from hazardous events or malicious attacks. In this paper a novel resilience metric for linear time invariant systems is proposed: the…

Systems and Control · Electrical Eng. & Systems 2021-08-23 Johannes Börner , Florian Steinke

This paper is devoted to the analysis of resonant MEMS sensors based on discrete relay feedback techniques. One drawback of such techniques is that some synchronization usually occurs between the discrete part and the continuous part of the…

Other Computer Science · Computer Science 2007-11-29 J. Juillard , E. Colinet , M. Dominguez , Joan Pons , J. Ricart