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In this note, we introduce a distributed twist on the classic coupon collector problem: a set of $m$ collectors wish to each obtain a set of $n$ coupons; for this, they can each sample coupons uniformly at random, but can also meet in…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-14 Dan Alistarh , Peter Davies

We study distributed algorithms that find a maximal matching in an anonymous, edge-coloured graph. If the edges are properly coloured with $k$ colours, there is a trivial greedy algorithm that finds a maximal matching in $k-1$ synchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-24 Juho Hirvonen , Jukka Suomela

Many combinatorial optimization problems can be phrased in the language of constraint satisfaction problems. We introduce a graph neural network architecture for solving such optimization problems. The architecture is generic; it works for…

Artificial Intelligence · Computer Science 2020-02-12 Jan Toenshoff , Martin Ritzert , Hinrikus Wolf , Martin Grohe

An effective technique for solving optimization problems over massive data sets is to partition the data into smaller pieces, solve the problem on each piece and compute a representative solution from it, and finally obtain a solution…

Data Structures and Algorithms · Computer Science 2015-06-23 Vahab Mirrokni , Morteza Zadimoghaddam

An important problem in computational topology is to calculate the homology of a space from samples. In this work, we develop a statistical approach to this problem by calculating the expected rank of an induced map on homology from a…

Computation · Statistics 2023-08-04 Tianyi Sun , Bradley Nelson

The optimization of dynamic problems is both widespread and difficult. When conducting dynamic optimization, a balance between reinitialization and computational expense has to be found. There are multiple approaches to this. In parallel…

Neural and Evolutionary Computing · Computer Science 2014-01-21 Ronald Hochreiter , Christoph Waldhauser

We study the problem of maximizing a submodular function, subject to a cardinality constraint, with a set of agents communicating over a connected graph. We propose a distributed greedy algorithm that allows all the agents to converge to a…

Optimization and Control · Mathematics 2020-09-29 Lintao Ye , Shreyas Sundaram

Auctions are widely used in exchanges to match buy and sell requests. Once the buyers and sellers place their requests, the exchange determines how these requests are to be matched. The two most popular objectives used while determining the…

Data Structures and Algorithms · Computer Science 2024-03-06 Mohit Garg , Suneel Sarswat

We consider optimization problems for complex systems in which the cost function has a multivalleyed landscape. We introduce a new class of dynamical algorithms which, using a suitable annealing procedure coupled with a balanced…

Mathematical Physics · Physics 2007-05-23 Pierluigi Contucci , Cristian Giardina' , Claudio Giberti , Cecilia Vernia

The classical alternating minimization (or projection) algorithm has been successful in the context of solving optimization problems over two variables. The iterative nature and simplicity of the algorithm has led to its application to many…

Information Theory · Computer Science 2010-08-24 Urs Niesen , Devavrat Shah , Gregory Wornell

Consider $n$ independent, biased coins, each with a known probability of heads. Presented with an ordering of these coins, flip (i.e., toss) each coin once, in that order, until we have observed both a *head* and a *tail*, or flipped all…

Data Structures and Algorithms · Computer Science 2025-10-21 Feyza Duman Keles , Lisa Hellerstein , Kunal Marwaha , Christopher Musco , Xinchen Yang

Consider a channel with a given input distribution. Our aim is to degrade it to a channel with at most L output letters. One such degradation method is the so called "greedy-merge" algorithm. We derive an upper bound on the reduction in…

Information Theory · Computer Science 2017-05-09 Assaf Kartowsky , Ido Tal

We examine the minimum entropy coupling problem, where one must find the minimum entropy variable that has a given set of distributions $S = \{p_1, \dots, p_m \}$ as its marginals. Although this problem is NP-Hard, previous works have…

Information Theory · Computer Science 2022-03-11 Spencer Compton

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

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

In mechanism design it is typical to impose incentive compatibility and then derive an optimal mechanism subject to this constraint. By replacing the incentive compatibility requirement with the goal of minimizing expected ex post regret,…

Computer Science and Game Theory · Computer Science 2012-08-07 Paul Duetting , Felix Fischer , Pitchayut Jirapinyo , John K. Lai , Benjamin Lubin , David C. Parkes

The counterfeit coin problem requires us to find all false coins from a given bunch of coins using a balance scale. We assume that the balance scale gives us only ``balanced'' or ``tilted'' information and that we know the number k of false…

Quantum Physics · Physics 2013-12-05 Kazuo Iwama , Harumichi Nishimura , Rudy Raymond , Junichi Teruyama

We study a natural combinatorial pricing problem for sequentially arriving buyers with equal budgets. Each buyer is interested in exactly one pair of items and purchases this pair if and only if, upon arrival, both items are still available…

Computer Science and Game Theory · Computer Science 2023-02-24 Christoph Dürr , Mathieu Mari , Ulrike Schmidt-Kraepelin

Identifying breakpoints in piecewise regression is critical in enhancing the reliability and interpretability of data fitting. In this paper, we propose novel algorithms based on the greedy algorithm to accurately and efficiently identify…

Machine Learning · Statistics 2026-04-14 Taehyeong Kim , Hyungu Lee , Myungjin Kim , Hayoung Choi

We investigate the performance of a deterministic GREEDY algorithm for the problem of maximizing functions under a partition matroid constraint. We consider non-monotone submodular functions and monotone subadditive functions. Even though…

Discrete Mathematics · Computer Science 2019-02-22 Tobias Friedrich , Andreas Göbel , Frank Neumann , Francesco Quinzan , Ralf Rothenberger