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Instance sparsification is well-known in the world of exact computation since it is very closely linked to the Exponential Time Hypothesis. In this paper, we extend the concept of sparsification in order to capture subexponential time…

Computational Complexity · Computer Science 2014-02-17 Edouard Bonnet , Vangelis Th. Paschos

We deal with the approximate solution of initial value problems in infinite-dimensional Banach spaces with a Schauder basis. We only allow finite-dimensional algorithms acting in the spaces $\rr^N$, with varying $N$. The error of such…

Numerical Analysis · Mathematics 2018-11-09 Boleslaw Kacewicz , Pawel Przybylowicz

Given a real symmetric positive semi-definite matrix E, and an approximation S that is a sum of n independent matrix-valued random variables, we present bounds on the relative error in S due to randomization. The bounds do not depend on the…

Numerical Analysis · Mathematics 2018-01-03 John T. Holodnak , Ilse C. F. Ipsen , Ralph C. Smith

We obtain a strengthening of the principle of local reflexivity in a general form. The added strength makes local reflexivity operators respect given subspaces. Applications are given to bounded approximation properties of pairs, consisting…

Functional Analysis · Mathematics 2013-10-24 Eve Oja

In this paper we analyze the approximation of stable linear time-invariant systems, like the Hilbert transform, by sampling series for bandlimited functions in the Paley-Wiener space $\mathcal{PW}_{\pi}^{1}$. It is known that there exist…

Information Theory · Computer Science 2015-05-13 Holger Boche , Ullrich J. Mönich

Subspace inference for neural networks assumes that a subspace of their parameter space suffices to produce a reliable uncertainty quantification. In this work, we underpin the validity of this assumption by using low rank techniques. We…

Machine Learning · Computer Science 2026-04-13 Josua Faller , Jörg Martin

We study how well a quasi-Banach space can be coarsely embedded into a Hilbert space. Given any quasi-Banach space X which coarsely embeds into a Hilbert space, we compute its Hilbert space compression exponent. We also show that the…

Functional Analysis · Mathematics 2015-11-18 Michal Kraus

We consider best approximation problems in a nonlinear subset $\mathcal{M}$ of a Banach space of functions $(\mathcal{V},\|\bullet\|)$. The norm is assumed to be a generalization of the $L^2$-norm for which only a weighted Monte Carlo…

Numerical Analysis · Mathematics 2021-05-13 Martin Eigel , Reinhold Schneider , Philipp Trunschke

Given a Banach space $X$ and a real number $\alpha\ge 1$, we write: (1) $D(X)\le\alpha$ if, for any locally finite metric space $A$, all finite subsets of which admit bilipschitz embeddings into $X$ with distortions $\le C$, the space $A$…

Functional Analysis · Mathematics 2019-10-10 Sofiya Ostrovska , Mikhail I. Ostrovskii

It was shown by G. Pisier that any finite-dimensional normed space admits an $\alpha$-regular $M$-position, guaranteeing not only regular entropy estimates but moreover regular estimates on the diameters of minimal sections of its unit-ball…

Functional Analysis · Mathematics 2021-05-28 Emanuel Milman , Yuval Yifrach

We study a quantity called discrete layered entropy, which approximates the Shannon entropy within a logarithmic gap. Compared to the Shannon entropy, the discrete layered entropy is piecewise linear, approximates the expected length of the…

Information Theory · Computer Science 2026-01-27 Cheuk Ting Li

Let X_1, ..., X_n be a sequence of n classical random variables and consider a sample of r positions selected at random. Then, except with (exponentially in r) small probability, the min-entropy of the sample is not smaller than, roughly, a…

Quantum Physics · Physics 2012-06-04 Robert Koenig , Renato Renner

In this article, we consider the problem of approximating a finite set of data (usually huge in applications) by invariant subspaces generated through a small set of smooth functions. The invariance is either by translations under a…

Optimization and Control · Mathematics 2023-11-22 Davide Barbieri , Eugenio Hernández , Carlos Cabrelli , Ursula Molter

We study the problem of {\em properly} learning large margin halfspaces in the agnostic PAC model. In more detail, we study the complexity of properly learning $d$-dimensional halfspaces on the unit ball within misclassification error…

Machine Learning · Computer Science 2019-08-30 Ilias Diakonikolas , Daniel M. Kane , Pasin Manurangsi

We study the problem of estimating the fixed point of a contractive operator defined on a separable Banach space. Focusing on a stochastic query model that provides noisy evaluations of the operator, we analyze a variance-reduced stochastic…

Statistics Theory · Mathematics 2022-11-30 Wenlong Mou , Koulik Khamaru , Martin J. Wainwright , Peter L. Bartlett , Michael I. Jordan

We solve the convergence case of the generalized Baker-Schmidt problem for simultaneous approximation on affine subspaces, under natural diophantine type conditions. In one of our theorems, we do not require monotonicity on the…

Number Theory · Mathematics 2020-01-08 Jing-Jing Huang , Jason J. Liu

Let $H$ be a Hilbert space and $H_1,...,H_n$ be closed subspaces of $H$. Denote by $P_k$ the orthogonal projection onto $H_k$, $k=1,2,...,n$. Following Patrick L. Combettes and Noli N. Reyes, we will say that the system of subspaces…

Functional Analysis · Mathematics 2020-02-07 Ivan Feshchenko

For Banach spaces $X,Y,$ we consider a distance problem in the space of bounded linear operators $\mathcal{L}(X,Y).$ Motivated by a recent paper \cite{RAO21}, we obtain sufficient conditions so that for a compact operator…

Functional Analysis · Mathematics 2022-03-22 Arpita Mal

We study the properties of "generic", in the sense of the Haar measure on the corresponding Grassmann manifold, subspaces of l^N_infinity of given dimension. We prove that every "well bounded" operator on such a subspace, say E, is a…

Functional Analysis · Mathematics 2016-09-06 P. Mankiewicz , Stanislaw J. Szarek

The Shapley value, and its broader family of semi-values, has received much attention in various attribution problems. A fundamental and long-standing challenge is their efficient approximation, since exact computation generally requires an…

Machine Learning · Computer Science 2026-04-10 Weida Li , Yaoliang Yu , Bryan Kian Hsiang Low