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Related papers: A characterization of bad approximability

200 papers

Venn-Abers predictors are probabilistic predictors that enjoy appealing properties of validity, but their major limitation is that they are applicable only to the case of binary classification, with a recent extension to bounded regression.…

Machine Learning · Computer Science 2026-05-08 Ivan Petej , Vladimir Vovk

We prove upper and lower bounds for certain sums of products of fractional parts by using majoring and minorizing functions from Fourier analysis. In special cases the upper bounds are sharp if there exist counterexamples to the Littlewood…

Number Theory · Mathematics 2013-09-09 Thai Hoang Le , Jeffrey D. Vaaler

We establish a framework for the study of the effective theory of weak convergence of measures. We define two effective notions of weak convergence of measures on $\mathbb{R}$: one uniform and one non-uniform. We show that these notions are…

Logic · Mathematics 2021-06-03 Timothy H. McNicholl , Diego A. Rojas

This paper deals with a modifed iterative projection method for approximating a solution of hierarchical fixed point problems for nearly nonexpansive mappings. Some strong convergence theorems for the proposed method are presented under…

Functional Analysis · Mathematics 2014-03-17 Ibrahim Karahan , Murat Ozdemir

We give an easy optimal bound for the dimension of the subspaces generated by the best Diophantine approximations.

Number Theory · Mathematics 2023-04-19 Nikolay Moshchevitin

Matrix completion algorithms recover a low rank matrix from a small fraction of the entries, each entry contaminated with additive errors. In practice, the singular vectors and singular values of the low rank matrix play a pivotal role for…

Methodology · Statistics 2016-05-03 Juhee Cho , Donggyu Kim , Karl Rohe

The statistical properties of the length of the cycles and of the weights of the attraction basins in fully asymmetric neural networks (i.e. with completely uncorrelated synapses) are computed in the framework of the annealed approximation…

Disordered Systems and Neural Networks · Physics 2009-10-30 U. Bastolla , G. Parisi

Consider a sample of a centered random vector with unit covariance matrix. We show that under certain regularity assumptions, and up to a natural scaling, the smallest and the largest eigenvalues of the empirical covariance matrix converge,…

Probability · Mathematics 2018-03-16 Djalil Chafaï , Konstantin Tikhomirov

In the present work we classify the relatively minimal 3-dimensional quasihomogeneous complex projective varieties under the assumption that the automorphism group is not solvable. By relatively minimal we understand varieties X having at…

Algebraic Geometry · Mathematics 2007-05-23 Stefan Kebekus

We present some new and explicit error bounds for the approximation of distributions. The approximation error is quantified by the maximal density ratio of the distribution $Q$ to be approximated and its proxy $P$. This non-symmetric…

Statistics Theory · Mathematics 2022-09-02 Lutz Duembgen , Richard Samworth , Jon Wellner

We study approximation in the unit interval by rational numbers whose numerators are selected randomly with certain probabilities. Previous work showed that an analogue of Khintchine's Theorem holds in a similar random model and raised the…

Number Theory · Mathematics 2019-09-17 Laima Kaziulytė , Felipe A. Ramírez

In this paper, explicit error bounds are derived in the approximation of rank $k$ projections of certain $n$-dimensional random vectors by standard $k$-dimensional Gaussian random vectors. The bounds are given in terms of $k$, $n$, and a…

Probability · Mathematics 2007-06-07 Elizabeth Meckes

We consider linear problems in the worst case setting. That is, given a linear operator and a pool of admissible linear measurements, we want to approximate the values of the operator uniformly on a convex and balanced set by means of…

Numerical Analysis · Mathematics 2024-03-05 David Krieg , Peter Kritzer

This monograph aims at presenting the core weak convergence theory for sequences of random vectors with values in $\mathbb{R}^k$. In some places, a more general formulation in metric spaces is provided. It lays out the necessary foundation…

Probability · Mathematics 2016-11-14 Gane Samb Lo

This paper addresses weak approximation for rationally connected varieties defined over the function field of a curve, especially at places of bad reduction. Our approach entails analyzing the rational connectivity of the smooth locus of…

Algebraic Geometry · Mathematics 2007-05-23 Brendan Hassett , Yuri Tschinkel

We generalize the optimal coupling theorem to multiple random variables: Given a collection of random variables, it is possible to couple all of them so that any two differ with probability comparable to the total-variation distance between…

Probability · Mathematics 2021-05-10 Omer Angel , Yinon Spinka

In a recent paper the author obtained optimal bounds for the strong Gaussian approximation of sums of independent $\R^d$-valued random vectors with finite exponential moments. The results may be considered as generalizations of well-known…

Probability · Mathematics 2007-05-23 A. Yu. Zaitsev

In this article, we prove a lower bound for the Hausdorff dimension of the set of exactly $\psi$-approximable vectors with values in a local field of positive characteristic. This is the analogue of the corresponding theorem of Bandi and de…

Number Theory · Mathematics 2025-03-11 Aratrika Pandey

In the theory of approximation there are some problems on approximation of compacts in functional spaces by nonlinear families : first we deal with the polynomial case, and then we consider the analytic case. We demonstrate a negative…

Functional Analysis · Mathematics 2007-05-23 Amadeo Irigoyen

Singular vectors are those for which the quality of rational approximations provided by Dirichlet's Theorem can be improved by arbitrarily small multiplicative constants. We provide an upper bound on the Hausdorff dimension of singular…

Dynamical Systems · Mathematics 2020-02-07 Osama Khalil