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We study an algorithm which has been proposed by Chinesta et al. to solve high-dimensional partial differential equations. The idea is to represent the solution as a sum of tensor products and to compute iteratively the terms of this sum.…

Analysis of PDEs · Mathematics 2013-09-18 José Arturo Infante Acevedo , Tony Lelievre

We present convergence estimates of two types of greedy algorithms in terms of the metric entropy of underlying compact sets. In the first part, we measure the error of a standard greedy reduced basis method for parametric PDEs by the…

Numerical Analysis · Mathematics 2024-10-29 Yuwen Li , Jonathan Siegel

Motivated by recent work on stochastic gradient descent methods, we develop two stochastic variants of greedy algorithms for possibly non-convex optimization problems with sparsity constraints. We prove linear convergence in expectation to…

Numerical Analysis · Mathematics 2014-07-02 Nam Nguyen , Deanna Needell , Tina Woolf

We introduce a greedy algorithm optimizing arrangements of lines with respect to a property. We apply this algorithm to the case of simpliciality: it recovers all known simplicial arrangements of lines in a very short time and also produces…

Combinatorics · Mathematics 2020-06-26 Michael Cuntz

The cosparse analysis model has been introduced recently as an interesting alternative to the standard sparse synthesis approach. A prominent question brought up by this new construction is the analysis pursuit problem -- the need to find a…

Functional Analysis · Mathematics 2014-01-06 Raja Giryes , Sangnam Nam , Michael Elad , Rémi Gribonval , Mike E. Davies

We analyze the performance of the greedy algorithm, and also a discrete semi-gradient based algorithm, for maximizing the sum of a suBmodular and suPermodular (BP) function (both of which are non-negative monotone non-decreasing) under two…

Discrete Mathematics · Computer Science 2018-01-24 Wenruo Bai , Jeffrey A. Bilmes

The frame algorithm uses a simple recursive formula to approximate an unknown vector from its frame coefficients. This note introduces an adaptive version of the frame algorithm that maximizes the error reduction between steps in terms of…

Functional Analysis · Mathematics 2025-06-24 Brody Dylan Johnson

In this paper, we propose the greedy and random Broyden's method for solving nonlinear equations. Specifically, the greedy method greedily selects the direction to maximize a certain measure of progress for approximating the current…

Numerical Analysis · Mathematics 2021-10-19 Haishan Ye , Dachao Lin , Zhihua Zhang

We prove that if $\mathcal{X}$ is a quasi-greedy Markushevich basis of a Banach space $\mathbb{X}$, its dual basis $\mathcal{X}^*$ spans a norming subspace of $\mathbb{X}^*$. We also prove this result for weaker forms of quasi-greediness,…

Functional Analysis · Mathematics 2025-10-09 Miguel Berasategui

It is known that for a conditional quasi-greedy basis $\mathcal{B}$ in a Banach space $\mathbb{X}$, the associated sequence $(k_{m}[\mathcal{B}])_{m=1}^{\infty}$ of its conditionality constants verifies the estimate…

Functional Analysis · Mathematics 2017-12-13 Fernando Albiac , José L. Ansorena

The nonlinear Kaczmarz method was recently proposed to solve the system of nonlinear equations. In this paper, we first discuss two greedy selection rules, i.e., the maximum residual and maximum distance rules, for the nonlinear Kaczmarz…

Numerical Analysis · Mathematics 2022-09-14 Yanjun Zhang , Hanyu Li , Ling Tang

For Schauder bases, Dilworth et al. introduced and characterized the partially greedy property, which is strictly weaker than the (almost) greedy property. Later, Berasategui et al. defined and studied the strong partially greedy property…

Functional Analysis · Mathematics 2024-05-14 Hung Viet Chu

The "classical" (weak) greedy algorithm is widely used within model order reduction in order to compute a reduced basis in the offline training phase: An a posteriori error estimator is maximized and the snapshot corresponding to the…

Numerical Analysis · Mathematics 2026-05-27 Niklas Reich , Karsten Urban , Jürgen Vorloeper

This article develops a new theoretical basis for decomposing signals that are formed by the linear superposition of a finite number of modes. Each mode depends nonlinearly upon several parameters; we seek both these parameters and the…

Metric Geometry · Mathematics 2021-06-09 Michael Robinson

In this article, we derive a novel convergence estimate for the weak POD-Greedy method with multiple POD modes and variable greedy thresholds in terms of the entropy numbers of the parametric solution manifold. Combining the POD with the…

Numerical Analysis · Mathematics 2025-01-15 Yuwen Li , Yupeng Wang

We analyse the problem of controllability for parameter-dependent linear finite-dimensional systems. The goal is to identify the most distinguished realisations of those parameters so to better describe or approximate the whole range of…

Optimization and Control · Mathematics 2016-10-07 Martin Lazar , Enrique Zuazua

The fact that finite direct sums of two or more mutually different spaces from the family $\{\ell_{p} : 1\le p<\infty\}\cup c_{0}$ fail to have greedy bases is stated in [Dilworth et al., Greedy bases for Besov spaces, Constr. Approx. 34…

Functional Analysis · Mathematics 2014-01-21 Fernando Albiac , José L. Ansorena

In nonlinear greedy approximation theory, bidemocratic bases have traditionally played the role of dualizing democratic, greedy, quasi-greedy, or almost greedy bases. In this article we shift the viewpoint and study them for their own sake,…

Functional Analysis · Mathematics 2021-06-01 Fernando Albiac , Jose L. Ansorena , Miguel Berasategui , Pablo M. Berna , Silvia Lassalle

We prove that the sequence spaces $\ell_p\oplus\ell_q$ and the spaces of infinite matrices $\ell_p(\ell_q)$, $\ell_q(\ell_p)$ and $(\bigoplus_{n=1}^\infty \ell_p^n)_{\ell_q}$, which are isomorphic to certain Besov spaces, have an almost…

Functional Analysis · Mathematics 2022-08-23 Fernando Albiac , José L. Ansorena , Glenier Bello , Przemysław Wojtaszczyk

Bayesian Reinforcement Learning (RL) is capable of not only incorporating domain knowledge, but also solving the exploration-exploitation dilemma in a natural way. As Bayesian RL is intractable except for special cases, previous work has…

Artificial Intelligence · Computer Science 2013-06-14 Kenji Kawaguchi , Mauricio Araya