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In many prediction problems, it is not uncommon that the number of variables used to construct a forecast is of the same order of magnitude as the sample size, if not larger. We then face the problem of constructing a prediction in the…

Statistics Theory · Mathematics 2016-02-08 Alessio Sancetta

In many machine learning applications, one needs to interactively select a sequence of items (e.g., recommending movies based on a user's feedback) or make sequential decisions in a certain order (e.g., guiding an agent through a series of…

Machine Learning · Computer Science 2019-06-21 Marko Mitrovic , Ehsan Kazemi , Moran Feldman , Andreas Krause , Amin Karbasi

The main goal of this paper is twofold. First, we extend some results known in the case of weak greedy algorithms with a scalar parameter to the case of weak greedy algorithms with a weakness sequence. Second, we formulate a new setting of…

Numerical Analysis · Mathematics 2026-04-30 A. S. Spivak , V. N. Temlyakov

We propose a general greedy algorithm for binary de Bruijn sequences, called Generalized Prefer-Opposite (GPO) Algorithm, and its modifications. By identifying specific feedback functions and initial states, we demonstrate that most…

Information Theory · Computer Science 2021-05-27 Zuling Chang , Martianus Frederic Ezerman , Adamas Aqsa Fahreza

A set $\mathcal S\subset \mathbb N$ is said to be a subset-sum-distinct or dissociated if all of its finite subsets have different sums. Alternately, an equivalent classification is if any equality of the form $$\sum_{s\in \mathcal S}…

Combinatorics · Mathematics 2026-02-06 Sayan Dutta

In this article, we present a family of numerical approaches to solve high-dimensional linear non-symmetric problems. The principle of these methods is to approximate a function which depends on a large number of variates by a sum of tensor…

Functional Analysis · Mathematics 2012-10-26 Eric Cances , Virginie Ehrlacher , Tony Lelievre

The submodular maximization problem is widely applicable in many engineering problems where objectives exhibit diminishing returns. While this problem is known to be NP-hard for certain subclasses of objective functions, there is a greedy…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-01 Haoyuan Sun , David Grimsman , Jason R Marden

The Column Subset Selection Problem provides a natural framework for unsupervised feature selection. Despite being a hard combinatorial optimization problem, there exist efficient algorithms that provide good approximations. The drawback of…

Machine Learning · Computer Science 2018-04-13 Bruno Ordozgoiti , Alberto Mozo , Jesús García López de Lacalle

The random greedy algorithm for finding a maximal independent set in a graph constructs a maximal independent set by inspecting the graph's vertices in a random order, adding the current vertex to the independent set if it is not adjacent…

Combinatorics · Mathematics 2023-09-28 Michael Krivelevich , Tamás Mészáros , Peleg Michaeli , Clara Shikhelman

This paper proposes a greedy heuristic named as Big step greedy heuristic and investigates the application of Big step greedy heuristic for maximum k-coverage problem. Greedy algorithms construct the solution in multiple steps, the…

Data Structures and Algorithms · Computer Science 2015-09-25 Drona Pratap Chandu

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

We consider Continuous Ordinary Differential Equations (CODE) y'=f(y), where f is a continuous function. They are known to always have solutions for a given initial condition y(0)=y0, these solutions being possibly non unique. We restrict…

Computational Complexity · Computer Science 2020-01-22 Olivier Bournez , Sabrina Ouazzani

Despite strong performance on a variety of tasks, neural sequence models trained with maximum likelihood have been shown to exhibit issues such as length bias and degenerate repetition. We study the related issue of receiving…

Machine Learning · Computer Science 2020-10-06 Sean Welleck , Ilia Kulikov , Jaedeok Kim , Richard Yuanzhe Pang , Kyunghyun Cho

In this work, we study the multi-agent decision problem where agents try to coordinate to optimize a given system-level objective. While solving for the global optimal is intractable in many cases, the greedy algorithm is a well-studied and…

Multiagent Systems · Computer Science 2022-12-01 Rohit Konda , David Grimsman , Jason Marden

The method of alternating projections involves projecting an element of a Hilbert space cyclically onto a collection of closed subspaces. It is known that the resulting sequence always converges in norm and that one can obtain estimates for…

Numerical Analysis · Mathematics 2019-02-14 Oscar Darwin , Aashraya Jha , Souktik Roy , David Seifert , Rhys Steele , Liam Stigant

We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest superstring of a finite set of strings $S$ is sought containing as a factor every string of $S$ or its reversal. We call this problem…

Data Structures and Algorithms · Computer Science 2015-12-08 Gabriele Fici , Tomasz Kociumaka , Jakub Radoszewski , Wojciech Rytter , Tomasz Waleń

In this paper, we describe how to get Janet decomposition for a finite set of terms and detect completeness of that set by means of the associated Bar Code. Moreover, we explain an algorithm to find a variable ordering (if it exists) s.t. a…

Combinatorics · Mathematics 2019-10-08 Michela Ceria

For any positive integers $h\ge 2$ and $g\ge 1$, we present a greedy algorithm that provides an infinite $B_h[g]$ sequence with $a_n\le 2gn^{h+(h-1)/g}.$

Combinatorics · Mathematics 2016-01-14 Javier Cilleruelo

This paper establishes a connection between a problem in Potential Theory and Mathematical Physics, arranging points so as to minimize an energy functional, and a problem in Combinatorics and Number Theory, constructing 'well-distributed'…

Mathematical Physics · Physics 2020-01-27 Florian Pausinger

Greedy algorithms are a fundamental category of algorithms in mathematics and computer science, characterized by their iterative, locally optimal decision-making approach, which aims to find global optima. In this review, we will discuss…

Functional Analysis · Mathematics 2024-12-09 Andrea García