Online algorithms achieve multiplicative approximation r^{1/(r-1)} for maximum independent sets in dense r-uniform ER hypergraphs and (max γ_i)^{-1/(r-1)} for balanced sets in r-partite versions, with matching lower bounds.
Graph structure via local occupancy,https://arxiv.org/abs/2003.14361 (preprint), 2020 (cit
4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
Transfer theorem converts max-degree independence bounds to average-degree bounds for hereditary uniform hypergraphs, with applications to cycle-free graphs and bounded-clique graphs.
For p = d/n the r-th power has maximum degree ~ log n over (r+1)-fold log and chromatic number sandwiched between the maximum degrees of the floor(r/2) and (r-1) powers plus one (equality at r=2); for d = omega(log n) up to n^{1/r-Omega(1)} the chromatic number is Theta(d^r / log d).
New degree-sequence lower bounds on hard-core independent set sizes via multivariate local occupancy and spectral analysis.
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Algorithmic Phase Transition for Large Independent Sets in Dense Hypergraphs
Online algorithms achieve multiplicative approximation r^{1/(r-1)} for maximum independent sets in dense r-uniform ER hypergraphs and (max γ_i)^{-1/(r-1)} for balanced sets in r-partite versions, with matching lower bounds.
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Hypergraph independence bounds: from maximum degree to average degree
Transfer theorem converts max-degree independence bounds to average-degree bounds for hereditary uniform hypergraphs, with applications to cycle-free graphs and bounded-clique graphs.
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Coloring powers of random graphs
For p = d/n the r-th power has maximum degree ~ log n over (r+1)-fold log and chromatic number sandwiched between the maximum degrees of the floor(r/2) and (r-1) powers plus one (equality at r=2); for d = omega(log n) up to n^{1/r-Omega(1)} the chromatic number is Theta(d^r / log d).
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Degree-sequence bounds for independent sets via multivariate local occupancy
New degree-sequence lower bounds on hard-core independent set sizes via multivariate local occupancy and spectral analysis.