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Ergodic Optimization is the process of finding invariant probability measures that maximize the integral of a given function. It has been conjectured that "most" functions are optimized by measures supported on a periodic orbit, and it has…

Dynamical Systems · Mathematics 2015-03-17 Anthony Quas , Jason Siefken

Fractional Sobolev spaces, also known as Besov or Slobodetzki spaces, arise in many areas of analysis, stochastic analysis in particular. We prove an embedding into certain q-variation spaces and discuss a few applications. First we show…

Probability · Mathematics 2007-05-23 Peter Friz , Nicolas Victoir

This paper deals with the fractional Sobolev spaces $W^{s, p}(\Omega)$, with $s\in (0, 1]$ and $p\in[1,+\infty]$. Here, we use the interpolation results in [4] to provide suitable conditions on the exponents $s$ and $p$ so that the spaces…

Analysis of PDEs · Mathematics 2024-11-20 Serena Dipierro , Edoardo Proietti Lippi , Caterina Sportelli , Enrico Valdinoci

A Sobolev type embedding for radially symmetric functions on the unit ball $B$ in $\mathbb R^n$, $n\geq 3$, into the variable exponent Lebesgue space $L_{2^\star + |x|^\alpha} (B)$, $2^\star = 2n/(n-2)$, $\alpha>0$, is known due to J.M. do…

Analysis of PDEs · Mathematics 2020-04-23 Quôc Anh Ngô , Van Hoang Nguyen

We prove compactness of the embeddings in Sobolev spaces for fractional super and sub harmonic functions with radial symmetry. The main tool is a pointwise decay for radially symmetric functions belonging to a function space defined by…

Functional Analysis · Mathematics 2022-01-25 Jacopo Bellazzini , Vladimir Georgiev

A key problem in approximation theory is the recovery of high-dimensional functions from samples. In many cases, the functions of interest exhibit anisotropic smoothness, and, in many practical settings, the nature of this anisotropy may be…

Numerical Analysis · Mathematics 2026-04-10 Ben Adcock , Avi Gupta

We study $L_q$-approximation and integration for functions from the Sobolev space $W^s_p(\Omega)$ and compare optimal randomized (Monte Carlo) algorithms with algorithms that can only use iid sample points, uniformly distributed on the…

Numerical Analysis · Mathematics 2021-08-05 David Krieg , Erich Novak , Mathias Sonnleitner

Function values are, in some sense, "almost as good" as general linear information for $L_2$-approximation (optimal recovery, data assimilation) of functions from a reproducing kernel Hilbert space. This was recently proved by new upper…

Numerical Analysis · Mathematics 2022-03-23 Aicke Hinrichs , David Krieg , Erich Novak , Jan Vybiral

We introduce the notion of decomposition space as a general framework for incidence algebras and M\"obius inversion: it is a simplicial infinity-groupoid satisfying an exactness condition weaker than the Segal condition, which expresses…

Category Theory · Mathematics 2015-12-25 Imma Gálvez-Carrillo , Joachim Kock , Andrew Tonks

We study multivariate approximation of periodic function in the worst case setting with the error measured in the $L_\infty$ norm. We consider algorithms that use standard information $\Lambda^{\rm std}$ consisting of function values or…

Numerical Analysis · Mathematics 2023-05-01 Jiaxin Geng , Heping Wang

In this paper, we focus on the problem of stochastic optimization where the objective function can be written as an expectation function over a closed convex set. We also consider multiple expectation constraints which restrict the domain…

Statistics Theory · Mathematics 2019-06-18 Kinjal Basu , Preetam Nandy

We develop new techniques for rounding packing integer programs using iterative randomized rounding. It is based on a novel application of multidimensional Brownian motion in $\mathbb{R}^n$. Let $\overset{\sim}{x} \in {[0,1]}^n$ be a…

Data Structures and Algorithms · Computer Science 2015-07-31 Dhiraj Madan , Sandeep Sen

The Metropolis algorithm is arguably the most fundamental Markov chain Monte Carlo (MCMC) method. But the algorithm is not guaranteed to converge to the desired distribution in the case of multivariate binary distributions (e.g., Ising…

Machine Learning · Statistics 2020-06-29 Kai Brügge , Asja Fischer , Christian Igel

We show that the M\"obius function of an interval in a permutation poset where the lower bound is sum (resp. skew) indecomposable depends solely on the sum (resp. skew) indecomposable permutations contained in the upper bound, and that this…

Combinatorics · Mathematics 2018-10-15 Robert Brignall , David Marchant

We derive the Christoffel-Geronimus-Uvarov transformations of a system of bi-orthogonal polynomials and associated functions on the unit circle, that is to say the modification of the system corresponding to a rational modification of the…

Classical Analysis and ODEs · Mathematics 2008-11-26 N. S. Witte

We develop a numerical approach for computing the additive, multiplicative and compressive convolution operations from free probability theory. We utilize the regularity properties of free convolution to identify (pairs of) `admissible'…

Probability · Mathematics 2013-07-22 Sheehan Olver , Raj Rao Nadakuditi

The ray transform $I$ integrates symmetric $m$-tensor field in $\mathbb{R}^n$ over lines. This transform in Sobolev spaces was studied in our earlier work where higher order Reshetnyak formulas (isometry relations) were established. The…

Analysis of PDEs · Mathematics 2024-01-11 Venky P. Krishnan , Vladimir A. Sharafutdinov

A new representation is proposed for functions in a Sobolev space with dominating mixed smoothness on an $N$-dimensional hyperrectangle. In particular, it is shown that these functions can be expressed in terms of their highest-order mixed…

Numerical Analysis · Mathematics 2024-04-30 Declan S. Jagt , Matthew M. Peet

We study multivariate numerical integration of smooth functions in weighted Sobolev spaces with dominating mixed smoothness $\alpha\geq 2$ defined over the $s$-dimensional unit cube. We propose a new quasi-Monte Carlo (QMC)-based quadrature…

Numerical Analysis · Mathematics 2019-12-09 Josef Dick , Takashi Goda , Takehito Yoshiki

Fixed a continuous kernel K on the $d$-dimensional torus, we consider a generalization of the univariate $sk$-spline to the torus, associated with the kernel K. It is proved an estimate which provides the rate of convergence of a given…

Functional Analysis · Mathematics 2018-04-10 Juliana Gaiba Oliveira , Sergio Antonio Tozoni