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We derive properties of powers of a function satisfying a second-order linear differential equation. In particular we prove that the n-th power of the function satisfies an (n+1)-th order differential equation and give a simple method for…

Classical Analysis and ODEs · Mathematics 2015-07-29 Naoki Marumo , Toshinori Oaku , Akimichi Takemura

Second order Sobolev metrics on the space of regular unparametrized planar curves have several desirable completeness properties not present in lower order metrics, but numerics are still largely missing. In this paper, we present…

Differential Geometry · Mathematics 2016-09-08 Martin Bauer , Martins Bruveris , Philipp Harms , Jakob Møller-Andersen

In this article, we introduce a novel concept for second-order information of a nonsmooth function inspired by the Goldstein eps-subdifferential. It comprises the coefficients of all existing second-order Taylor expansions in an eps-ball…

Optimization and Control · Mathematics 2025-01-06 Bennet Gebken

Linear statistics of eigenvalues in many familiar classes of random matrices are known to obey gaussian central limit theorems. The proofs of such results are usually rather difficult, involving hard computations specific to the model in…

Probability · Mathematics 2007-11-25 Sourav Chatterjee

We derive novel concentration inequalities that bound the statistical error for a large class of stochastic optimization problems, focusing on the case of unbounded objective functions. Our derivations utilize the following key tools: 1) A…

Machine Learning · Statistics 2026-01-01 Jeremiah Birrell

We characterize the restrictions of first order Sobolev functions to regular subsets of a homogeneous metric space and prove the existence of the corresponding linear extension operator.

Functional Analysis · Mathematics 2007-05-23 Pavel Shvartsman

The concentration of measure phenomenon may be summarized as follows: a function of many weakly dependent random variables that is not too sensitive to any of its individual arguments will tend to take values very close to its expectation.…

Probability · Mathematics 2016-11-18 Aryeh Kontorovich , Maxim Raginsky

The Dirichlet forms methods, in order to represent errors and their propagation, are particularly powerful in infinite dimensional problems such as models involving stochastic analysis encountered in finance or physics, cf. [5]. Now, coming…

Probability · Mathematics 2016-11-04 Nicolas Bouleau

Classical geometric mechanics, including the study of symmetries, Lagrangian and Hamiltonian mechanics, and the Hamilton-Jacobi theory, are founded on geometric structures such as jets, symplectic and contact ones. In this paper, we shall…

Mathematical Physics · Physics 2023-06-09 Qiao Huang , Jean-Claude Zambrini

The concentration of measure phenomena were discovered as the mathematical background of statistical mechanics at the end of the XIX - beginning of the XX century and were then explored in mathematics of the XX-XXI centuries. At the…

Machine Learning · Computer Science 2018-03-20 A. N. Gorban , I. Y. Tyukin

Second order approximate ancillaries have evolved as the primary ingredient for recent likelihood development in statistical inference. This uses quantile functions rather than the equivalent distribution functions, and the intrinsic…

Statistics Theory · Mathematics 2010-11-29 Ailana M. Fraser , D. A. S. Fraser , Ana-Maria Staicu

Via operator theoretic methods, we formalize the concentration phenomenon for a given observable `$r$' of a discrete time Markov chain with `$\mu_{\pi}$' as invariant ergodic measure, possibly having support on an unbounded state space. The…

Machine Learning · Computer Science 2023-06-01 Muhammad Abdullah Naeem , Miroslav Pajic

We establish concentration inequalities for random dynamical systems (RDSs), assuming that the observables of interest are separately Lipschitz. Under a weak average contraction condition, we obtain deviation bounds for several random…

Dynamical Systems · Mathematics 2026-03-24 Graccyela Salcedo

In this paper we consider stochastic composite convex optimization problems with the objective function satisfying a stochastic bounded gradient condition, with or without a quadratic functional growth property. These models include the…

Optimization and Control · Mathematics 2020-03-10 Ion Necoara

We analyze the behavior of stochastic approximation algorithms where iterates, in expectation, progress towards an objective at each step. When progress is proportional to the step size of the algorithm, we prove exponential concentration…

Machine Learning · Statistics 2024-03-26 Kody Law , Neil Walton , Shangda Yang

We prove a curvature-dimension criterion and obtain logarithmic Sobolev inequalities for generalised Cauchy measures with optimal weights and explicit constants. In the one-dimensional case, this constant is even optimal. From these…

Functional Analysis · Mathematics 2026-04-06 Baptiste Nicolas Huguet

Consider an ergodic stationary random field $A$ on the ambient space $\mathbb R^d$. In a companion article, we introduced the notion of multiscale (first-order) functional inequalities, which extend standard functional inequalities like…

Probability · Mathematics 2019-10-11 Mitia Duerinckx , Antoine Gloria

We present the second-order general relativistic description of the observed galaxy number density in a cosmological framework. The observed galaxy number density is affected by the volume and the source effects, both of which arise due to…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 Jaiyul Yoo , Matias Zaldarriaga

We prove concentration inequalities for $f\left( X\right) $ about its median, where $X$ is a random vector in $\mathbb{R}^n$ with independent heavy tailed coordinates of Weibull or power type, and $f:\mathbb{R}^n\rightarrow\mathbb{R}$ is a…

Probability · Mathematics 2022-08-12 Daniel J. Fresen

Anomalies are known to appear in the perturbation theory for the one-dimensional Anderson model. A systematic approach to anomalies at critical points of products of random matrices is developed, classifying and analysing their possible…

Mathematical Physics · Physics 2007-05-23 Hermann Schulz-Baldes
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