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Electronic Colloquium on Computational Complexity

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REPORTS > KEYWORD > BOUNDED DEGREE GRAPHS:
Reports tagged with bounded degree graphs:
TR00-021 | 19th April 2000
Uriel Feige, Marek Karpinski, Michael Langberg

Improved Approximation of MAX-CUT on Graphs of Bounded Degree

We analyze the addition of a simple local improvement step to various known
randomized approximation algorithms.
Let $\alpha \simeq 0.87856$ denote the best approximation ratio currently
known for the Max Cut problem on general graphs~\cite{GW95}.
We consider a semidefinite relaxation of the Max Cut problem,
round it using the ... more >>>


TR06-089 | 16th July 2006
Sofya Raskhodnikova, Adam Smith

A Note on Adaptivity in Testing Properties of Bounded Degree Graphs

We show that in the bounded degree model for graph property testing,
adaptivity is essential. An algorithm is *non-adaptive* if it makes all queries to the input before receiving any answers. We call a property *non-trivial* if it does not depend only on the degree distribution of the nodes. We ... more >>>


TR18-101 | 20th May 2018
Akash Kumar, C. Seshadhri, Andrew Stolman

Finding forbidden minors in sublinear time: a $O(n^{1/2+o(1)})$-query one-sided tester for minor closed properties on bounded degree graphs

Let $G$ be an undirected, bounded degree graph with $n$ vertices. Fix a finite graph $H$, and suppose one must remove $\varepsilon n$ edges from $G$ to make it $H$-minor free (for some small constant $\varepsilon > 0$).
We give an $n^{1/2+o(1)}$-time randomized procedure that, with high probability, finds an ... more >>>


TR18-148 | 25th August 2018
Akash Kumar, C. Seshadhri, Andrew Stolman

Finding forbidden minors in sublinear time: a $n^{1/2+o(1)}$-query one-sided tester for minor closed properties on bounded degree graphs

Let $G$ be an undirected, bounded degree graph
with $n$ vertices. Fix a finite graph $H$, and suppose one must remove $\varepsilon n$ edges from $G$ to make it $H$-minor free (for some small constant $\varepsilon > 0$). We give an $n^{1/2+o(1)}$-time randomized procedure that, with high probability, finds an ... more >>>




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