4,284 research outputs found
Incremental Maintenance of Maximal Cliques in a Dynamic Graph
We consider the maintenance of the set of all maximal cliques in a dynamic
graph that is changing through the addition or deletion of edges. We present
nearly tight bounds on the magnitude of change in the set of maximal cliques,
as well as the first change-sensitive algorithms for clique maintenance, whose
runtime is proportional to the magnitude of the change in the set of maximal
cliques. We present experimental results showing these algorithms are efficient
in practice and are faster than prior work by two to three orders of magnitude.Comment: 18 pages, 8 figure
On the Enumeration of all Minimal Triangulations
We present an algorithm that enumerates all the minimal triangulations of a
graph in incremental polynomial time. Consequently, we get an algorithm for
enumerating all the proper tree decompositions, in incremental polynomial time,
where "proper" means that the tree decomposition cannot be improved by removing
or splitting a bag
An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths
A chordless cycle (induced cycle) of a graph is a cycle without any
chord, meaning that there is no edge outside the cycle connecting two vertices
of the cycle. A chordless path is defined similarly. In this paper, we consider
the problems of enumerating chordless cycles/paths of a given graph
and propose algorithms taking time for each chordless cycle/path. In
the existing studies, the problems had not been deeply studied in the
theoretical computer science area, and no output polynomial time algorithm has
been proposed. Our experiments showed that the computation time of our
algorithms is constant per chordless cycle/path for non-dense random graphs and
real-world graphs. They also show that the number of chordless cycles is much
smaller than the number of cycles. We applied the algorithm to prediction of
NMR (Nuclear Magnetic Resonance) spectra, and increased the accuracy of the
prediction
Spectral Bounds for the Connectivity of Regular Graphs with Given Order
The second-largest eigenvalue and second-smallest Laplacian eigenvalue of a
graph are measures of its connectivity. These eigenvalues can be used to
analyze the robustness, resilience, and synchronizability of networks, and are
related to connectivity attributes such as the vertex- and edge-connectivity,
isoperimetric number, and characteristic path length. In this paper, we present
two upper bounds for the second-largest eigenvalues of regular graphs and
multigraphs of a given order which guarantee a desired vertex- or
edge-connectivity. The given bounds are in terms of the order and degree of the
graphs, and hold with equality for infinite families of graphs. These results
answer a question of Mohar.Comment: 24 page
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