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We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the private local objective of an agent in a network with time-varying topology. The local objectives have distinct…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-10-09 Annie I. Chen , Asuman Ozdaglar

In the NP-hard \textsc{Group Closeness Centrality Maximization} problem, the input is a graph $G = (V,E)$ and a positive integer $k$, and the task is to find a set $S \subseteq V$ of size $k$ that maximizes the reciprocal of group farness…

Data Structures and Algorithms · Computer Science 2026-03-27 Christian Schulz , Jakob Ternes , Henning Woydt

This work studies a class of non-smooth decentralized multi-agent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common non-smooth term. We propose a general primal-dual…

Optimization and Control · Mathematics 2020-07-13 Sulaiman A. Alghunaim , Ernest K. Ryu , Kun Yuan , Ali H. Sayed

The classic lower bound of Kuhn, Moscibroda and Wattenhofer [JACM 2016] states that approximate maximum matching and approximate vertex cover (among other problems) in the LOCAL model require $\Omega(\min\{\sqrt{\frac{\log n}{\log\log n}},…

Data Structures and Algorithms · Computer Science 2026-05-14 Peter Davies-Peck

$k$-Coloring Reconfiguration is one of the most well-studied reconfiguration problems, which asks to transform a given proper $k$-coloring of a graph to another by repeatedly recoloring a single vertex. Its approximate version, Maxmin…

Computational Complexity · Computer Science 2025-04-01 Shuichi Hirahara , Naoto Ohsaka

We present a $(1+\frac{k}{k+2})$-approximation algorithm for the Maximum $k$-dependent Set problem on bipartite graphs for any $k\ge1$. For a graph with $n$ vertices and $m$ edges, the algorithm runs in $O(k m \sqrt{n})$ time and improves…

Combinatorics · Mathematics 2021-10-07 Seyedmohammadhossein Hosseinian , Sergiy Butenko

Consider the following stochastic matching problem. Given a graph $G=(V, E)$, an unknown subgraph $G_p = (V, E_p)$ is realized where $E_p$ includes every edge of $E$ independently with some probability $p \in (0, 1]$. The goal is to query a…

Data Structures and Algorithms · Computer Science 2025-06-25 Amir Azarmehr , Soheil Behnezhad , Alma Ghafari , Ronitt Rubinfeld

The local minimum degree of a graph is the minimum degree that can be reached by means of local complementation. For any n, there exist graphs of order n which have a local minimum degree at least 0.189n, or at least 0.110n when restricted…

Discrete Mathematics · Computer Science 2016-08-18 David Cattanéo , Simon Perdrix

We show a deterministic constant-time local algorithm for constructing an approximately maximum flow and minimum fractional cut in multisource-multitarget networks with bounded degrees and bounded edge capacities. Locality means that the…

Data Structures and Algorithms · Computer Science 2023-11-03 Endre Csóka , András Pongrácz

This papers studies multi-agent (convex and \emph{nonconvex}) optimization over static digraphs. We propose a general distributed \emph{asynchronous} algorithmic framework whereby i) agents can update their local variables as well as…

Optimization and Control · Mathematics 2019-09-12 Ye Tian , Ying Sun , Gesualdo Scutari

We consider two models of computation: centralized local algorithms and local distributed algorithms. Algorithms in one model are adapted to the other model to obtain improved algorithms. Distributed vertex coloring is employed to design…

Data Structures and Algorithms · Computer Science 2014-11-12 Guy Even , Moti Medina , Dana Ron

We consider distributed convex optimization problems that involve a separable objective function and nontrivial functional constraints, such as Linear Matrix Inequalities (LMIs). We propose a decentralized and computationally inexpensive…

Optimization and Control · Mathematics 2018-01-22 Soomin Lee , Michael M. Zavlanos

Bilevel optimization has been developed for many machine learning tasks with large-scale and high-dimensional data. This paper considers a constrained bilevel optimization problem, where the lower-level optimization problem is convex with…

Machine Learning · Computer Science 2023-08-22 Siyuan Xu , Minghui Zhu

We consider the graph $k$-partitioning problem under the min-max objective, termed as Minmax $k$-cut. The input here is a graph $G=(V,E)$ with non-negative edge weights $w:E\rightarrow \mathbb{R}_+$ and an integer $k\geq 2$ and the goal is…

Data Structures and Algorithms · Computer Science 2020-11-09 Karthekeyan Chandrasekaran , Weihang Wang

We consider a multi-agent optimization problem where agents subject to local, intermittent interactions aim to minimize a sum of local objective functions subject to a global inequality constraint and a global state constraint set. In…

Optimization and Control · Mathematics 2012-10-10 Minghui Zhu , Sonia Martinez

We consider a multi-agent framework for distributed optimization where each agent has access to a local smooth strongly convex function, and the collective goal is to achieve consensus on the parameters that minimize the sum of the agents'…

Multiagent Systems · Computer Science 2020-04-23 Mahmoud Assran , Michael Rabbat

A $z$-matching on a bipartite graph is a set of edges, among which each vertex of two types of the graph is adjacent to at most $1$ and at most $z$ ($\geqslant 1$) edges, respectively. The $z$-matching problem concerns finding $z$-matchings…

Physics and Society · Physics 2023-05-30 Jin-Hua Zhao

Given a set of $m$ agents and a set of $n$ items, where agent $A$ has utility $u_{A,i}$ for item $i$, our goal is to allocate items to agents to maximize fairness. Specifically, the utility of an agent is the sum of its utilities for items…

Data Structures and Algorithms · Computer Science 2009-01-05 Deeparnab Chakrabarty , Julia Chuzhoy , Sanjeev Khanna

The densest subgraph problem is a classic problem in combinatorial optimisation. Danisch, Chan, and Sozio propose a definition for \emph{local density} that assigns to each vertex $v$ a value $\rho^*(v)$. This local density is a…

Data Structures and Algorithms · Computer Science 2024-11-22 Aleksander Bjørn Christiansen , Ivor van der Hoog , Eva Rotenberg

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos