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A Distributed (2 + ε)-Approximation for Vertex Cover in O(log Δ / ε log log Δ) Rounds

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1006/jagm.1994.1036openalex-snapshot
A Primal-Dual Parallel Approximation Technique Applied to Weighted Set and Vertex Covers
inferredcites →https://doi.org/10.1007/978-1-4684-2001-2_9openalex-snapshot
Reducibility among Combinatorial Problems
inferredcites →https://doi.org/10.1007/978-3-030-36826-5_4openalex-snapshot
Introduction to Algorithms
inferredcites →https://doi.org/10.1007/978-3-642-04355-0_21openalex-snapshot
A Local 2-Approximation Algorithm for the Vertex Cover Problem
inferredcites →https://doi.org/10.1007/bf01580444openalex-snapshot
Vertex packings: Structural properties and algorithms
inferredcites →https://doi.org/10.1007/pl00008932openalex-snapshot
Some simple distributed algorithms for sparse networks
inferredcites →https://doi.org/10.1007/s00446-011-0127-7openalex-snapshot
Distributed algorithms for covering, packing and maximum weighted matching
inferredcites →https://doi.org/10.1007/s004530010009openalex-snapshot
One for the Price of Two: a Unified Approach for Approximating Covering Problems
inferredcites →https://doi.org/10.1016/0196-6774(81)90020-1openalex-snapshot
A linear-time approximation algorithm for the weighted vertex cover problem
inferredcites →https://doi.org/10.1016/j.ipl.2009.02.017openalex-snapshot
A simple local 3-approximation algorithm for vertex cover
inferredcites →https://doi.org/10.1016/j.jcss.2007.06.019openalex-snapshot
Vertex cover might be hard to approximate to within 2−ε
inferredcites →https://doi.org/10.1016/j.jpdc.2011.12.003openalex-snapshot
Distributed approximation of cellular coverage
inferredcites →https://doi.org/10.1016/s0019-9958(86)80023-7openalex-snapshot
Deterministic coin tossing with applications to optimal parallel list ranking
inferredcites →https://doi.org/10.1016/s0304-0208(08)73101-3openalex-snapshot
A Local-Ratio Theorem for Approximating the Weighted Vertex Cover Problem
inferredcites →https://doi.org/10.1109/focs.2012.60openalex-snapshot
The Locality of Distributed Symmetry Breaking
inferredcites →https://doi.org/10.1109/focs.2016.72openalex-snapshot
An Exponential Separation between Randomized and Deterministic Complexity in the LOCAL Model
inferredcites →https://doi.org/10.1137/0211045openalex-snapshot
Approximation Algorithms for the Set Covering and Vertex Cover Problems
inferredcites →https://doi.org/10.1137/050625382openalex-snapshot
On the Equivalence between the Primal-Dual Schema and the Local Ratio Technique
inferredcites →https://doi.org/10.1137/06065310xopenalex-snapshot
A Primal-Dual Bicriteria Distributed Algorithm for Capacitated Vertex Cover
inferredcites →https://doi.org/10.1137/s0895480100373121openalex-snapshot
On the Distributed Complexity of Computing Maximal Matchings
inferredcites →https://doi.org/10.1145/1011767.1011811openalex-snapshot
What cannot be computed locally!
inferredcites →https://doi.org/10.1145/1435375.1435381openalex-snapshot
Distributed weighted vertex cover via maximal matchings
inferredcites →https://doi.org/10.1145/1810479.1810533openalex-snapshot
Fast distributed approximation algorithms for vertex cover and set cover in anonymous networks
inferredcites →https://doi.org/10.1145/2742012openalex-snapshot
Local Computation
inferredcites →https://doi.org/10.1145/2903137openalex-snapshot
The Locality of Distributed Symmetry Breaking
inferredcites →https://doi.org/10.48550/arxiv.1506.05093openalex-snapshot
An Improved Distributed Algorithm for Maximal Independent Set
inferredcites →https://doi.org/10.48550/arxiv.1608.03220openalex-snapshot
Distributed Degree Splitting, Edge Coloring, and Orientations

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-030-01325-7_21openalex-snapshot
A Deterministic Distributed 2-Approximation for Weighted Vertex Cover in $$O(\log N\log \varDelta /\log ^2\log \varDelta )$$ Rounds
inferred← citeshttps://doi.org/10.1007/978-3-031-20350-3_9openalex-snapshot
Computing Connected-k-Subgraph Cover with Connectivity Requirement
inferred← citeshttps://doi.org/10.1007/978-3-031-60603-8_16openalex-snapshot
Distributed Fractional Local Ratio and Independent Set Approximation
inferred← citeshttps://doi.org/10.1007/s00446-025-00486-8openalex-snapshot
Towards distributed two-stage stochastic optimization
inferred← citeshttps://doi.org/10.1016/j.ic.2024.105238openalex-snapshot
Distributed fractional local ratio and independent set approximation
inferred← citeshttps://doi.org/10.1016/j.jocs.2021.101518openalex-snapshot
A localized distributed algorithm for vertex cover problem
inferred← citeshttps://doi.org/10.1017/s0960129523000439openalex-snapshot
Approximation Algorithm and FPT Algorithm for Connected-k-Subgraph Cover on Minor-Free Graphs
inferred← citeshttps://doi.org/10.1109/focs.2017.23openalex-snapshot
A Time Hierarchy Theorem for the LOCAL Model
inferred← citeshttps://doi.org/10.1109/icdcsw63273.2025.00025openalex-snapshot
A Fast-Converging Decentralized Approach to the Weighted Minimum Vertex Cover Problem
inferred← citeshttps://doi.org/10.1109/iscas51556.2021.9401117openalex-snapshot
A Minimal Memory Game-Based Distributed Algorithm to Vertex Cover of Networks
inferred← citeshttps://doi.org/10.1109/tsmc.2021.3121695openalex-snapshot
Better Approximation for Distributed Weighted Vertex Cover via Game-Theoretic Learning
inferred← citeshttps://doi.org/10.1137/17m1117537openalex-snapshot
An Exponential Separation between Randomized and Deterministic Complexity in the LOCAL Model
inferred← citeshttps://doi.org/10.1137/17m1157957openalex-snapshot
A Time Hierarchy Theorem for the LOCAL Model
inferred← citeshttps://doi.org/10.1145/3293611.3331577openalex-snapshot
Optimal Distributed Covering Algorithms
inferred← citeshttps://doi.org/10.1145/3300150.3300166openalex-snapshot
SIROCCO 2018 Review
inferred← citeshttps://doi.org/10.1145/3382734.3405750openalex-snapshot
Distributed Approximation on Power Graphs
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