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It is a survey on recent results in constructive sparse approximation. Three directions are discussed here: (1) Lebesgue-type inequalities for greedy algorithms with respect to a special class of dictionaries, (2) constructive sparse…

Numerical Analysis · Mathematics 2015-11-06 Vladimir Temlyakov

We introduce the notion of a \textit{weight-almost greedy} basis and show that a basis for a real Banach space is $w$-almost greedy if and only if it is both quasi-greedy and $w$-democratic. We also introduce the notion of…

Functional Analysis · Mathematics 2018-03-09 Stephen J. Dilworth , Denka Kutzarova , Vladimir Temlyakov , Ben Wallis

It is known that a basis is almost greedy if and only if the thresholding greedy algorithm gives essentially the smallest error term compared to errors from projections onto intervals or in other words, consecutive terms of $\mathbb{N}$. In…

Functional Analysis · Mathematics 2025-02-12 Miguel Berasategui , Pablo M. Berná , Hung Viet Chu

We study greedy-type algorithms such that at a greedy step we pick several dictionary elements contrary to a single dictionary element in standard greedy-type algorithms. We call such greedy algorithms {\it super greedy algorithms}. The…

Numerical Analysis · Mathematics 2010-10-27 Entao Liu , Vladimir N. Temlyakov

We present new results regarding Lebesgue-type inequalities for the Weak Chebyshev Greedy Algorithm (WCGA) in uniformly smooth Banach spaces. We improve earlier bounds in Temlyakov (Forum Math Sigma 2014), for dictionaries satisfying a new…

Functional Analysis · Mathematics 2019-10-01 Stephen Dilworth , Gustavo Garrigos , Eugenio Hernandez , Denka Kutzarova , Vladimir Temlyakov

We characterize the approximation spaces of a broad class of bases - which includes almost greedy bases - in terms of weighted Lorentz spaces. For those bases, we also find necessary and sufficient conditions under which the approximation…

Functional Analysis · Mathematics 2025-02-17 Miguel Berasategui , Pablo M. Berná , Andrea García

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

We briefly discuss the greedy method and a couple of its more efficient variants for approximately maximizing monotone submodular functions.

Optimization and Control · Mathematics 2025-10-21 Alen Alexanderian

Clustering problems such as $k$-means and $k$-median are staples of unsupervised learning, and many algorithmic techniques have been developed to tackle their numerous aspects. In this paper, we focus on the class of greedy approximation…

Data Structures and Algorithms · Computer Science 2025-10-30 Max Dupré la Tour , David Saulpic

We shall present new characterizations of partially greedy and almost greedy bases. A new class of basis (which we call reverse partially greedy basis) arises naturally from these characterizations of partially greedy bases. We also give…

Functional Analysis · Mathematics 2018-05-18 S. J. Dilworth , Divya Khurana

It is known that greedy methods perform well for maximizing monotone submodular functions. At the same time, such methods perform poorly in the face of non-monotonicity. In this paper, we show - arguably, surprisingly - that invoking the…

Machine Learning · Computer Science 2017-04-07 Moran Feldman , Christopher Harshaw , Amin Karbasi

Chebyshev Greedy Algorithm is a generalization of the well known Orthogonal Matching Pursuit defined in a Hilbert space to the case of Banach spaces. We apply this algorithm for constructing sparse approximate solutions (with respect to a…

Machine Learning · Statistics 2013-12-05 Vladimir Temlyakov

We study sparse approximation by greedy algorithms. We prove the Lebesgue-type inequalities for the Weak Chebyshev Greedy Algorithm (WCGA), a generalization of the Weak Orthogonal Matching Pursuit to the case of a Banach space. The main…

Machine Learning · Statistics 2013-03-28 Vladimir Temlyakov

We shall present a new characterization of greedy bases and 1-greedy bases in terms of certain functionals defined using distances to one dimensional subspaces generated by the basis. We also introduce a new property that unifies the…

Functional Analysis · Mathematics 2016-04-26 Pablo M. Berná , Óscar Blasco

This paper describes a simple greedy D-approximation algorithm for any covering problem whose objective function is submodular and non-decreasing, and whose feasible region can be expressed as the intersection of arbitrary (closed upwards)…

Data Structures and Algorithms · Computer Science 2015-06-02 Christos Koufogiannakis , Neal E. Young

Given a Banach space X and one of its compact sets F, we consider the problem of finding a good n dimensional space X_n \subset X which can be used to approximate the elements of F. The best possible error we can achieve for such an…

Functional Analysis · Mathematics 2012-04-12 Ronald DeVore , Guergana Petrova , Przemyslaw Wojtaszczyk

Recently, it has been discovered that results on universal sampling discretization of the square norm are useful in sparse sampling recovery with error being measured in the square norm. It was established that a simple greedy type…

Numerical Analysis · Mathematics 2023-07-11 F. Dai , V. Temlyakov

We propose and analyze batch greedy heuristics for cardinality constrained maximization of non-submodular non-decreasing set functions. We consider the standard greedy paradigm, along with its distributed greedy and stochastic greedy…

Optimization and Control · Mathematics 2021-08-12 Jayanth Jagalur-Mohan , Youssef Marzouk

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

A deterministic approximation algorithm is presented for the maximization of non-monotone submodular functions over a ground set of size $n$ subject to cardinality constraint $k$; the algorithm is based upon the idea of interlacing two…

Data Structures and Algorithms · Computer Science 2019-10-28 Alan Kuhnle