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We consider the following stochastic matching problem on both weighted and unweighted graphs: A graph $G(V, E)$ along with a parameter $p \in (0, 1)$ is given in the input. Each edge of $G$ is realized independently with probability $p$.…

Data Structures and Algorithms · Computer Science 2018-11-09 Soheil Behnezhad , Alireza Farhadi , MohammadTaghi Hajiaghayi , Nima Reyhani

One of the most important open problems in machine scheduling is the problem of scheduling a set of jobs on unrelated machines to minimize the makespan. The best known approximation algorithm for this problem guarantees an approximation…

Discrete Mathematics · Computer Science 2015-03-17 José Verschae , Andreas Wiese

Finding a maximum cut is a fundamental task in many computational settings. Surprisingly, it has been insufficiently studied in the classic distributed settings, where vertices communicate by synchronously sending messages to their…

Data Structures and Algorithms · Computer Science 2017-07-27 Keren Censor-Hillel , Rina Levy , Hadas Shachnai

In a bipartite max-min LP, we are given a bipartite graph $\myG = (V \cup I \cup K, E)$, where each agent $v \in V$ is adjacent to exactly one constraint $i \in I$ and exactly one objective $k \in K$. Each agent $v$ controls a variable…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-05-15 Patrik Floréen , Marja Hassinen , Petteri Kaski , Jukka Suomela

OBDD-based graph algorithms deal with the characteristic function of the edge set E of a graph $G = (V,E)$ which is represented by an OBDD and solve optimization problems by mainly using functional operations. We present an OBDD-based…

Data Structures and Algorithms · Computer Science 2015-04-16 Marc Bury

We consider a natural generalization of scheduling $n$ jobs on $m$ parallel machines so as to minimize the makespan. In our extension the set of jobs is partitioned into several classes and a machine requires a setup whenever it switches…

Data Structures and Algorithms · Computer Science 2018-09-28 Klaus Jansen , Marten Maack , Alexander Mäcker

We provide a simple new randomized contraction approach to the global minimum cut problem for simple undirected graphs. The contractions exploit 2-out edge sampling from each vertex rather than the standard uniform edge sampling. We…

Data Structures and Algorithms · Computer Science 2019-09-04 Mohsen Ghaffari , Krzysztof Nowicki , Mikkel Thorup

Deep learning has been effectively applied to many discrete optimization problems. However, learning-based scheduling on unrelated parallel machines remains particularly difficult to design. Not only do the numbers of jobs and machines…

Machine Learning · Computer Science 2025-12-23 Diego Hitzges , Guillaume Sagnol

We consider the maximum bipartite matching problem in stochastic settings, namely the query-commit and price-of-information models. In the query-commit model, an edge e independently exists with probability $p_e$. We can query whether an…

Data Structures and Algorithms · Computer Science 2019-10-15 Buddhima Gamlath , Sagar Kale , Ola Svensson

We present the first near optimal approximation schemes for the maximum weighted (uncapacitated or capacitated) $b$--matching problems for non-bipartite graphs that run in time (near) linear in the number of edges. For any…

Data Structures and Algorithms · Computer Science 2018-06-19 Kook Jin Ahn , Sudipto Guha

The input to the Multiway Cut problem is a weighted undirected graph, with nonnegative edge weights, and $k$ designated terminals. The goal is to partition the vertices of the graph into $k$ parts, each containing exactly one of the…

Data Structures and Algorithms · Computer Science 2026-03-31 Joshua Brakensiek , Neng Huang , Aaron Potechin , Uri Zwick

Many real-life planning problems require making a priori decisions before all parameters of the problem have been revealed. An important special case of such problem arises in scheduling problems, where a set of tasks needs to be assigned…

Data Structures and Algorithms · Computer Science 2016-07-11 David Adjiashvili , Viktor Bindewald , Dennis Michaels

We present a simple nonadaptive randomized algorithm that estimates the number of edges in a simple, unweighted, undirected graph, possibly containing isolated vertices, using only degree and random edge queries. For an $n$-vertex graph,…

Data Structures and Algorithms · Computer Science 2025-12-16 Arijit Bishnu , Debarshi Chanda , Buddha Dev Das , Arijit Ghosh , Gopinath Mishra

In Constrained Correlation Clustering, the goal is to cluster a complete signed graph in a way that minimizes the number of negative edges inside clusters plus the number of positive edges between clusters, while respecting hard constraints…

Data Structures and Algorithms · Computer Science 2025-11-05 Nate Veldt

In graph signal processing, data samples are associated to vertices on a graph, while edge weights represent similarities between those samples. We propose a convex optimization problem to learn sparse well connected graphs from data. We…

Signal Processing · Electrical Eng. & Systems 2020-04-21 Eduardo Pavez , Antonio Ortega

We give polynomial-time algorithms for the exact computation of lowest-energy (ground) states, worst margin violators, log partition functions, and marginal edge probabilities in certain binary undirected graphical models. Our approach…

Machine Learning · Computer Science 2009-09-29 Nicol N. Schraudolph , Dmitry Kamenetsky

We study the performance of sequential contention resolution and matching algorithms on random graphs with vanishing edge probabilities. When the edges of the graph are processed in an adversarially-chosen order, we derive a new OCRS that…

Data Structures and Algorithms · Computer Science 2024-10-10 Will Ma , Calum MacRury , Pranav Nuti

The maximization for the independence systems defined on graphs is a generalization of combinatorial optimization problems such as the maximum $b$-matching, the unweighted MAX-SAT, the matchoid, and the maximum timed matching problems. In…

Data Structures and Algorithms · Computer Science 2022-08-23 Yuki Amano

An independent dominating set D of a graph G = (V,E) is a subset of vertices such that every vertex in V \ D has at least one neighbor in D and D is an independent set, i.e. no two vertices of D are adjacent in G. Finding a minimum…

Data Structures and Algorithms · Computer Science 2010-09-08 Serge Gaspers , Mathieu Liedloff

We give deterministic distributed $(1+\epsilon)$-approximation algorithms for Minimum Vertex Coloring and Maximum Independent Set on chordal graphs in the LOCAL model. Our coloring algorithm runs in $O(\frac{1}{\epsilon} \log n)$ rounds,…

Data Structures and Algorithms · Computer Science 2018-05-15 Christian Konrad , Viktor Zamaraev