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Given $m \ge 2$ discrete probability distributions over $n$ states each, the minimum-entropy coupling is the minimum-entropy joint distribution whose marginals are the same as the input distributions. Computing the minimum-entropy coupling…

Information Theory · Computer Science 2025-09-30 Spencer Compton

The Matching Augmentation Problem (MAP) has recently received significant attention as an important step towards better approximation algorithms for finding cheap $2$-edge connected subgraphs. This has culminated in a…

Data Structures and Algorithms · Computer Science 2022-08-25 Etienne Bamas , Marina Drygala , Ola Svensson

We study connections between the problem of fully dynamic $(1-\epsilon)$-approximate maximum bipartite matching, and the dual $(1+\epsilon)$-approximate vertex cover problem, with the online matrix-vector ($\mathsf{OMv}$) conjecture which…

Data Structures and Algorithms · Computer Science 2024-03-06 Yang P. Liu

Densest Subgraph Problem (DSP) is an important primitive problem with a wide range of applications, including fraud detection, community detection and DNA motif discovery. Edge-based density is one of the most common metrics in DSP.…

Databases · Computer Science 2023-10-31 Yugao Zhu , Shenghua Liu , Wenjie Feng , Xueqi Cheng

We consider the maximum matching problem in the semi-streaming model formalized by Feigenbaum, Kannan, McGregor, Suri, and Zhang that is inspired by giant graphs of today. As our main result, we give a two-pass $(1/2 + 1/16)$-approximation…

Data Structures and Algorithms · Computer Science 2017-04-24 Sagar Kale , Sumedh Tirodkar

This paper presents an algorithm for estimating the weight of a maximum weighted matching by augmenting any estimation routine for the size of an unweighted matching. The algorithm is implementable in any streaming model including dynamic…

Data Structures and Algorithms · Computer Science 2015-07-10 Marc Bury , Chris Schwiegelshohn

In the \textsc{Maximum Degree Contraction} problem, input is a graph $G$ on $n$ vertices, and integers $k, d$, and the objective is to check whether $G$ can be transformed into a graph of maximum degree at most $d$, using at most $k$ edge…

Data Structures and Algorithms · Computer Science 2020-09-25 Saket Saurabh , Prafullkumar Tale

We propose a fully dynamic algorithm for maintaining reachability information in directed graphs. The proposed deterministic dynamic algorithm has an update time of $O((ins*n^{2}) + (del * (m+n*log(n))))$ where $m$ is the current number of…

Data Structures and Algorithms · Computer Science 2007-11-22 Venkata Seshu Kumar Kurapati

We present the first polynomial self-stabilizing algorithm for finding a $\frac23$-approximation of a maximum matching in a general graph. The previous best known algorithm has been presented by Manne \emph{et al.} \cite{ManneMPT11} and has…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-21 Johanne Cohen , Khaled Maâmra , George Manoussakis , Laurence Pilard

A semi-streaming algorithm in dynamic graph streams processes any $n$-vertex graph by making one or multiple passes over a stream of insertions and deletions to edges of the graph and using $O(n \cdot \mbox{polylog}(n))$ space.…

Data Structures and Algorithms · Computer Science 2024-07-31 Sepehr Assadi , Soheil Behnezhad , Christian Konrad , Kheeran K. Naidu , Janani Sundaresan

Single Source Shortest Paths ($\textrm{SSSP}$) is among the most well-studied problems in computer science. In the incremental (resp. decremental) setting, the goal is to maintain distances from a fixed source in a graph undergoing edge…

Data Structures and Algorithms · Computer Science 2024-07-16 Barna Saha , Virginia Vassilevska Williams , Yinzhan Xu , Christopher Ye

Many dynamic graph algorithms have an amortized update time, rather than a stronger worst-case guarantee. But amortized data structures are not suitable for real-time systems, where each individual operation has to be executed quickly. For…

Data Structures and Algorithms · Computer Science 2021-03-12 Aaron Bernstein , Sebastian Forster , Monika Henzinger

We develop a new algorithmic technique that allows to transfer some constant time approximation algorithms for general graphs into random order streaming algorithms. We illustrate our technique by proving that in random order streams with…

Data Structures and Algorithms · Computer Science 2017-11-15 Pan Peng , Christian Sohler

The diameter, radius and eccentricities are natural graph parameters. While these problems have been studied extensively, there are no known dynamic algorithms for them beyond the ones that follow from trivial recomputation after each…

Data Structures and Algorithms · Computer Science 2019-12-18 Bertie Ancona , Monika Henzinger , Liam Roditty , Virginia Vassilevska Williams , Nicole Wein

Natural policy gradient (NPG) methods are among the most widely used policy optimization algorithms in contemporary reinforcement learning. This class of methods is often applied in conjunction with entropy regularization -- an algorithmic…

Machine Learning · Statistics 2022-09-13 Shicong Cen , Chen Cheng , Yuxin Chen , Yuting Wei , Yuejie Chi

Finding optimal matchings in dense graphs is of general interest and of particular importance in social, transportation and biological networks. While developing optimal solutions for various matching problems is important, the running…

Data Structures and Algorithms · Computer Science 2020-11-16 Nitish K. Panigrahy , Prithwish Basu , Don Towsley

The problem of finding the degeneracy of a graph is a subproblem of the k-core decomposition problem. In this paper, we present a (1 + epsilon)-approximate solution to the degeneracy problem which runs in O(n log n) time, sublinear in the…

Data Structures and Algorithms · Computer Science 2022-11-16 Valerie King , Alex Thomo , Quinton Yong

We give a fully dynamic algorithm maintaining a $(1-\varepsilon)$-approximate directed densest subgraph in $\tilde{O}(\log^3(n)/\varepsilon^6)$ amortized time or $\tilde{O}(\log^4(n)/\varepsilon^7)$ worst-case time per edge update (where…

Data Structures and Algorithms · Computer Science 2023-12-19 Richard Li , Kent Quanrud

Several distributed frameworks have been developed to scale Graph Neural Networks (GNNs) on billion-size graphs. On several benchmarks, we observe that the graph partitions generated by these frameworks have heterogeneous data distributions…

Machine Learning · Computer Science 2023-11-07 Dhruv Deshmukh , Gagan Raj Gupta , Manisha Chawla , Vishwesh Jatala , Anirban Haldar

An edge-weighted graph $G=(V,E)$ is called stable if the value of a maximum-weight matching equals the value of a maximum-weight fractional matching. Stable graphs play an important role in some interesting game theory problems, such as…

Data Structures and Algorithms · Computer Science 2017-11-28 Zhuan Khye Koh , Laura Sanità
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