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In [Temme N.M., Special functions. An introduction to the classical functions of mathematical physics, A Wiley-Interscience Publication, John Wiley & Sons, Inc., New York, 1996, Section 11.3.3.1] a uniform asymptotic expansion for the…

Classical Analysis and ODEs · Mathematics 2016-10-26 Gergő Nemes , Adri B. Olde Daalhuis

A class of distortions termed functional Bregman divergences is defined, which includes squared error and relative entropy. A functional Bregman divergence acts on functions or distributions, and generalizes the standard Bregman divergence…

Information Theory · Computer Science 2007-07-13 B. A. Frigyik , S. Srivastava , M. R. Gupta

We compare possibilities of extension of bounded and unbounded Baire-one functions from subspaces of topological spaces.

General Topology · Mathematics 2018-10-30 Olena Karlova , Volodymyr Mykhaylyuk

We study discrete probabilistic programs with potentially unbounded looping behaviors over an infinite state space. We present, to the best of our knowledge, the first decidability result for the problem of determining whether such a…

Logic in Computer Science · Computer Science 2022-06-22 Mingshuai Chen , Joost-Pieter Katoen , Lutz Klinkenberg , Tobias Winkler

We study the distance in the Zygmund class $\Lambda_{\ast}$ to the subspace $\operatorname{I}(\operatorname{BMO})$ of functions with distributional derivative with bounded mean oscillation. In particular, we describe the closure of…

Classical Analysis and ODEs · Mathematics 2019-08-14 Artur Nicolau , Odí Soler i Gibert

We prove that every nonnegative continuous real-valued function on a given compact metric space is the uniform limit of some increasing sequence of nonnegative simple functions being linear combinations of indicators of open sets; here the…

General Mathematics · Mathematics 2020-10-21 Yu-Lin Chou

We provide sufficient conditions on a family of functions $(\phi_\alpha)_{\alpha\in A}:\mathbb{R}^d\to\mathbb{R}$ for sampling of multivariate bandlimited functions at certain nonuniform sequences of points in $\mathbb{R}^d$. We consider…

Functional Analysis · Mathematics 2018-02-14 Keaton Hamm

We consider a class of "box-like" statistically self-affine functions, and compute the almost-sure box-counting dimension of their graphs. Furthermore, we consider the differentiability of our functions, and prove that, depending on an…

Classical Analysis and ODEs · Mathematics 2023-06-21 Pieter Allaart , Taylor Jones

In this paper, using the tools from the lineability theory, we distinguish certain subsets of $p$-adic differentiable functions. Specifically, we show that the following sets of functions are large enough to contain an infinite dimensional…

Nearest neighbor cells in $R^d,d\in\mathbb{N}$, are used to define coefficients of divergence ($\phi$-divergences) between continuous multivariate samples. For large sample sizes, such distances are shown to be asymptotically normal with a…

Probability · Mathematics 2009-03-06 Yu. Baryshnikov , Mathew D. Penrose , J. E. Yukich

Generalization under distribution shift remains a core challenge in modern machine learning, yet existing learning bound theory is limited to narrow, idealized settings and is non-estimable from samples. In this paper, we bridge the gap…

Machine Learning · Statistics 2025-08-25 Hongbo Chen , Li Charlie Xia

We study the property of global-local mixing for full-branched expanding maps of either the half-line or the interval, with one indifferent fixed point. Global-local mixing expresses the decorrelation of global vs local observables w.r.t.…

Dynamical Systems · Mathematics 2024-05-10 Giovanni Canestrari , Marco Lenci

Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. We pay special attention to the case of trigonometric polynomials with frequencies from an arbitrary finite set…

Numerical Analysis · Mathematics 2021-12-14 Boris Kashin , Sergei Konyagin , Vladimir Temlyakov

Within the study of uncertain dynamical systems, iterated random functions are a key tool. There, one samples a family of functions according to a stationary distribution. Here, we introduce an extension, where one sample functions…

Probability · Mathematics 2019-09-24 Ramen Ghosh , Jakub Marecek , Robert Shorten

A space $G(M, \varPhi)$ of infinitely differentiable functions in ${\mathbb R}^n$ constructed with a help of a family $\varPhi=\{\varphi_m\}_{m=1}^{\infty}$ of real-valued functions $\varphi_m \in~C({\mathbb R}^n)$ and a logarithmically…

Complex Variables · Mathematics 2017-12-15 I. Kh. Musin , P. V. Yakovleva

Maximum Mean Discrepancy (MMD) has been widely used in the areas of machine learning and statistics to quantify the distance between two distributions in the $p$-dimensional Euclidean space. The asymptotic property of the sample MMD has…

Statistics Theory · Mathematics 2023-08-29 Hanjia Gao , Xiaofeng Shao

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral

In this paper, we are concerned with a fractional differential inequality containing a lower order fractional derivative and a polynomial source term in the right hand side. A non-existence of non-trivial global solutions result is proved…

Classical Analysis and ODEs · Mathematics 2016-05-25 Mohammed Kassim , Khaled M. Furati , Nasser-eddine Tatar

In this paper, we introduce and investigate a class P of continuous and periodic functions on R. The class P is defined so that second-order central differences of a function satisfy some concavity-type estimate. Although this definition…

Classical Analysis and ODEs · Mathematics 2019-08-05 Yasuhiro Fujita , Nao Hamamuki , Antonio Siconolfi , Norikazu Yamaguchi

We define a generalized likelihood function based on uncertainty measures and show that maximizing such a likelihood function for different measures induces different types of classifiers. In the probabilistic framework, we obtain…

Machine Learning · Computer Science 2013-01-18 Loo-Nin Teow , Kia-Fock Loe
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