Introduces a distributed stochastic setting for graph optimization and supplies fast approximation algorithms for matching, vertex cover, and dominating set that surpass non-stochastic lower bounds.
Improved approximation algorithms for the vertex cover problem in graphs and hypergraphs
2 Pith papers cite this work. Polarity classification is still indexing.
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n/log n-approximation for MaxMin ISR on general graphs, polynomial-time approximation on degenerate graphs, FPT-AS on bounded-treewidth and H-minor-free graphs, plus inapproximability on bounded-degree, bandwidth n^{1/2+Θ(1)}, and bipartite graphs.
citing papers explorer
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Distributed Stochastic Graph Algorithms
Introduces a distributed stochastic setting for graph optimization and supplies fast approximation algorithms for matching, vertex cover, and dominating set that surpass non-stochastic lower bounds.
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On (In)approximability of MaxMin Independent Set Reconfiguration
n/log n-approximation for MaxMin ISR on general graphs, polynomial-time approximation on degenerate graphs, FPT-AS on bounded-treewidth and H-minor-free graphs, plus inapproximability on bounded-degree, bandwidth n^{1/2+Θ(1)}, and bipartite graphs.