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Convergent Sequences of Dense Graphs I: Subgraph Frequencies, Metric Properties and Testing
We consider sequences of graphs and define various notions of convergence
related to these sequences: ``left convergence'' defined in terms of the
densities of homomorphisms from small graphs into the graphs of the sequence,
and ``right convergence'' defined in terms of the densities of homomorphisms
from the graphs of the sequence into small graphs; and convergence in a
suitably defined metric.
In Part I of this series, we show that left convergence is equivalent to
convergence in metric, both for simple graphs, and for graphs with nodeweights
and edgeweights. One of the main steps here is the introduction of a
cut-distance comparing graphs, not necessarily of the same size. We also show
how these notions of convergence provide natural formulations of Szemeredi
partitions, sampling and testing of large graphs.Comment: 57 pages. See also http://research.microsoft.com/~borgs/. This
version differs from an earlier version from May 2006 in the organization of
the sections, but is otherwise almost identica
Rearranging trees for robust consensus
In this paper, we use the H2 norm associated with a communication graph to
characterize the robustness of consensus to noise. In particular, we restrict
our attention to trees and by systematic attention to the effect of local
changes in topology, we derive a partial ordering for undirected trees
according to the H2 norm. Our approach for undirected trees provides a
constructive method for deriving an ordering for directed trees. Further, our
approach suggests a decentralized manner in which trees can be rearranged in
order to improve their robustness.Comment: Submitted to CDC 201
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