English
Related papers

Related papers: Renorming spaces with greedy bases

200 papers

A greedy algorithm is proposed for sparse-sensor selection in reduced-order sensing that contains correlated noise in measurement. The sensor selection is carried out by maximizing the determinant of the Fisher information matrix in a…

Optimization and Control · Mathematics 2021-04-28 Keigo Yamada , Yuji Saito , Koki Nankai , Taku Nonomura , Keisuke Asai , Daisuke Tsubakino

The study of greedy approximation in the context of convex optimization is becoming a promising research direction as greedy algorithms are actively being employed to construct sparse minimizers for convex functions with respect to given…

Numerical Analysis · Mathematics 2022-04-26 Anton Dereventsov , Vladimir Temlyakov

Rearrangement-invariance in function spaces can be viewed as a kind of generalization of 1-symmetry for Schauder bases. We define subrearrangement-invariance in function spaces as an analogous generalization of 1-subsymmetry. It is then…

Functional Analysis · Mathematics 2021-01-06 Ben Wallis

A Banach space (or its norm) is said to have the diameter $2$ property (D$2$P in short) if every nonempty relatively weakly open subset of its closed unit ball has diameter $2$. We construct an equivalent norm on $L_1[0,1]$ which is weakly…

Functional Analysis · Mathematics 2022-12-29 Olav Nygaard , Märt Põldvere , Stanimir Troyansky , Tauri Viil

Let $\mathcal{F}$ be a hereditary collection of finite subsets of $\mathbb{N}$. In this paper, we introduce and characterize $\mathcal{F}$-(almost) greedy bases. Given such a family $\mathcal{F}$, a basis $(e_n)_n$ for a Banach space $X$ is…

Functional Analysis · Mathematics 2022-12-23 Kevin Beanland , Hung Viet Chu

The aim of this note is to present two results that make the task of finding equivalent polyhedral norms on certain Banach spaces, having either a Schauder basis or an uncountable unconditional basis, easier and more transparent. The…

Functional Analysis · Mathematics 2022-06-14 Trond A. Abrahamsen , Vladimir P. Fonf , Richard J. Smith , Stanimir Troyanski

Greedy algorithms are widely used for problems in machine learning such as feature selection and set function optimization. Unfortunately, for large datasets, the running time of even greedy algorithms can be quite high. This is because for…

Machine Learning · Statistics 2017-03-09 Rajiv Khanna , Ethan Elenberg , Alexandros G. Dimakis , Sahand Negahban , Joydeep Ghosh

The aim of this note is to complement and extend some recent results on Whitley's indices of thinness and thickness in three main directions. Firstly, we investigate both the indices when forming $\ell_p$-sums of Banach spaces, and obtain…

Functional Analysis · Mathematics 2014-05-28 Trond A. Abrahamsen , Johann Langemets , Vegard Lima , Olav Nygaard

It was previously known that the almost greedy (AG) property essentially remains the same when we enlarge greedy sums in the classical definition by a factor $\lambda \geqslant 1$. The present paper shows that if instead, we enlarge greedy…

Functional Analysis · Mathematics 2025-12-11 Hung Viet Chu

Many algorithms for maximizing a monotone submodular function subject to a knapsack constraint rely on the natural greedy heuristic. We present a novel refined analysis of this greedy heuristic which enables us to: $(1)$ reduce the…

Data Structures and Algorithms · Computer Science 2021-03-16 Ariel Kulik , Roy Schwartz , Hadas Shachnai

It is shown that a separable Banach space $X$ can be given an equivalent norm $|\!|\!|\cdot |\!|\!|$ with the following properties:\quad If $(x_n)\subseteq X$ is relatively weakly compact and $\lim_{m\to\infty} \lim_{n\to\infty}\break…

Functional Analysis · Mathematics 2016-09-07 Edward Odell , Thomas Schlumprecht

In 1999, S. V. Konyagin and V. N. Temlyakov introduced the so-called Thresholding Greedy Algorithm. Since then, there have been many interesting and useful characterizations of greedy-type bases in Banach spaces. In this article, we study…

Functional Analysis · Mathematics 2022-06-30 Pablo M. Berná , Hung Viet Chu

This paper is a follow up to the previous author's paper on convex optimization. In that paper we began the process of adjusting greedy-type algorithms from nonlinear approximation for finding sparse solutions of convex optimization…

Machine Learning · Statistics 2012-06-05 V. N. Temlyakov

Many image processing applications benefited remarkably from the theory of sparsity. One model of sparsity is the cosparse analysis one. It was shown that using l_1-minimization one might stably recover a cosparse signal from a small set of…

Numerical Analysis · Mathematics 2015-02-10 Raja Giryes

One classical result in greedy approximation theory is that almost-greedy and semi-greedy bases are equivalent in the context of Schauder bases in Banach spaces with finite cotype. This result was proved by S. J. Dilworth, N. J. Kalton and…

Functional Analysis · Mathematics 2019-03-01 Pablo M. Berná

The realisation of sensing modalities based on the principles of compressed sensing is often hindered by discrepancies between the mathematical model of its sensing operator, which is necessary during signal recovery, and its actual…

Information Theory · Computer Science 2018-02-21 Valerio Cambareri , Amirafshar Moshtaghpour , Laurent Jacques

The aim of this paper is to present two tools, Theorems 4 and 7, that make the task of finding equivalent polyhedral norms on certain Banach spaces easier and more transparent. The hypotheses of both tools are based on countable…

Functional Analysis · Mathematics 2016-11-04 V. P. Fonf , A. J. Pallares , R. J. Smith , S. Troyanski

We give a criterion ensuring that the elementary class of a modular Banach space E (that is, the class of Banach spaces, some ultrapower of which is linearly isometric to an ultrapower of E) consists of all direct sums E\oplus_m H, where H…

Functional Analysis · Mathematics 2017-03-28 C. Ward Henson , Yves Raynaud

This paper defines weak-$\alpha$-supermodularity for set functions. Many optimization objectives in machine learning and data mining seek to minimize such functions under cardinality constrains. We prove that such problems benefit from a…

Data Structures and Algorithms · Computer Science 2015-02-24 Christos Boutsidis , Edo Liberty , Maxim Sviridenko

We study sparse approximate solutions to convex optimization problems. It is known that in many engineering applications researchers are interested in an approximate solution of an optimization problem as a linear combination of elements…

Machine Learning · Statistics 2012-06-05 V. N. Temlyakov