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The purpose of this paper is to introduce $\omega$-Chebyshev-greedy and $\omega$-partially greedy approximation classes and to study their relation with $\omega$-approximation spaces, where the latter are a generalization of the classical…

Functional Analysis · Mathematics 2023-03-17 Pablo M. Berná , Hung Viet Chu , Eugenio Hernández

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

In the Shortest Common Superstring problem (SCS), one needs to find the shortest superstring for a set of strings. While SCS is NP-hard and MAX-SNP-hard, the Greedy Algorithm "choose two strings with the largest overlap; merge them; repeat"…

Data Structures and Algorithms · Computer Science 2021-02-11 Maksim Nikolaev

In the context of Gaussian conditioning, greedy algorithms iteratively select the most informative measurements, given an observed Gaussian random variable. However, the convergence analysis for conditioning Gaussian random variables…

Statistics Theory · Mathematics 2025-02-18 Daniel Winkle , Ingo Steinwart , Bernard Haasdonk

The purpose of this paper is to establish the almost sure weak ergodic convergence of a sequence of iterates $(x_n)$ given by $x_{n+1} = (I+\lambda_n A(\xi_{n+1},\,.\,))^{-1}(x_n)$ where $(A(s,\,.\,):s\in E)$ is a collection of maximal…

Optimization and Control · Mathematics 2016-07-26 Pascal Bianchi

Decision Tree is a classic formulation of active learning: given $n$ hypotheses with nonnegative weights summing to 1 and a set of tests that each partition the hypotheses, output a decision tree using the provided tests that uniquely…

Data Structures and Algorithms · Computer Science 2019-10-23 Ray Li , Percy Liang , Stephen Mussmann

A {\em subsequence} of a word $w$ is a word $u$ that can be obtained by deleting some letters from $w$ while maintaining the relative order of the remaining letters, e.g., $\mathtt{lala}$ is a subsequence of $\mathtt{alfalfa}$. A word, over…

Formal Languages and Automata Theory · Computer Science 2025-09-01 Duncan Adamson , Pamela Fleischmann , Annika Huch , Florin Manea , Paul Sarnighausen-Cahn , Max Wiedenhöft

In dictionary selection, several atoms are selected from finite candidates that successfully approximate given data points in the sparse representation. We propose a novel efficient greedy algorithm for dictionary selection. Not only does…

Machine Learning · Computer Science 2018-09-10 Kaito Fujii , Tasuku Soma

Closeness is a widely-used centrality measure in social network analysis. For a node it indicates the reciprocal of the average shortest-path distance to the other nodes of the network. While the identification of the k nodes with highest…

Data Structures and Algorithms · Computer Science 2019-05-16 Elisabetta Bergamini , Tanya Gonser , Henning Meyerhenke

We discuss the upper and lower estimates for the rate of convergence of Pure and Orthogonal Greedy Algorithms for dictionary with bounded cumulative coherence.

Numerical Analysis · Mathematics 2009-11-10 Eugene Livshitz

Let $\beta\in(1,2)$ and $x\in [0,\frac{1}{\beta-1}]$. We call a sequence $(\epsilon_{i})_{i=1}^\infty\in\{0,1\}^{\mathbb{N}}$ a $\beta$-expansion for $x$ if $x=\sum_{i=1}^{\infty}\epsilon_{i}\beta^{-i}$. We call a finite sequence…

Number Theory · Mathematics 2014-09-10 Simon Baker

Coherent uncertainty quantification is a key strength of Bayesian methods. But modern algorithms for approximate Bayesian posterior inference often sacrifice accurate posterior uncertainty estimation in the pursuit of scalability. This work…

Machine Learning · Statistics 2018-05-30 Trevor Campbell , Tamara Broderick

We consider in this paper a class of single-ratio fractional minimization problems, in which the numerator part of the objective is the sum of a nonsmooth nonconvex function and a smooth nonconvex function while the denominator part is a…

Optimization and Control · Mathematics 2020-12-23 Na Zhang , Qia Li

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

Given a set of strings, the shortest common superstring problem is to find the shortest possible string that contains all the input strings. The problem is NP-hard, but a lot of work has gone into designing approximation algorithms for…

Data Structures and Algorithms · Computer Science 2019-12-04 Jarno Alanko , Tuukka Norri

Let $\{X, X_n, n\geq 1\}$ be a sequence of independent identically distributed non-degenerate random variables. Put $S_0=0, S_n = \sum^n_{i=1} X_i$ and $V_n^2=\sum^n_{i=1} X_i^2, n\ge 1.$ A weak convergence theorem is established for the…

Probability · Mathematics 2013-06-21 Miklós Csörgő , Zhishui Hu

In this paper, we propose a unified framework and an algorithm for the problem of group recommendation where a fixed number of items or alternatives can be recommended to a group of users. The problem of group recommendation arises…

Information Retrieval · Computer Science 2017-12-27 Shameem A Puthiya Parambath , Nishant Vijayakumar , Sanjay Chawla

In this paper, we prove the following result: {quote} Let $\A$ be an infinite set of positive integers. For all positive integer $n$, let $\tau_n$ denote the smallest element of $\A$ which does not divide $n$. Then we have $$\lim_{N \to +…

Number Theory · Mathematics 2009-12-15 Bakir Farhi

We study the fundamental limits of matching pursuit, or the pure greedy algorithm, for approximating a target function $ f $ by a linear combination $f_n$ of $n$ elements from a dictionary. When the target function is contained in the…

Machine Learning · Statistics 2024-07-24 Jason M. Klusowski , Jonathan W. Siegel

We describe an adaptive greedy algorithm for Thiele continued-fraction approximation of a function defined on a continuum domain in the complex plane. The algorithm iteratively selects interpolation nodes from an adaptively refined set of…

Numerical Analysis · Mathematics 2025-10-09 Tobin A. Driscoll , Yuxing Zhou