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Conference

International Symposium on Algorithms and Computation 

About: International Symposium on Algorithms and Computation is an academic conference. The conference publishes majorly in the area(s): Time complexity & Approximation algorithm. Over the lifetime, 2222 publications have been published by the conference receiving 25116 citations.


Papers
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Proceedings Article
01 Jan 1976

502 citations

Book ChapterDOI
16 Dec 1999
TL;DR: This work considers online routing strategies for routing between the vertices of embedded planar straight line graphs and proposes two deterministic memoryless routing strategies and a randomized memoryless strategy that works for all triangulations.
Abstract: We consider online routing strategies for routing between the vertices of embedded planar straight line graphs. Our results include (1) two deterministic memoryless routing strategies, one that works for all Delaunay triangulations and the other that works for all regular triangulations, (2) a randomized memoryless strategy that works for all triangulations, (3) an O(1) memory strategy that works for all convex subdivisions, (4) an O(1) memory strategy that approximates the shortest path in Delaunay triangulations, and (5) theoretical and experimental results on the competitiveness of these strategies.

268 citations

Book ChapterDOI
15 Dec 2010
TL;DR: In this article, a nearly optimal fixed-parameter tractable algorithm for enumerating all maximal cliques, parametrized by degeneracy, was presented, which runs in time O(dn3 d/3).
Abstract: The degeneracy of an n-vertex graph G is the smallest number d such that every subgraph of G contains a vertex of degree at most d. We show that there exists a nearly-optimal fixed-parameter tractable algorithm for enumerating all maximal cliques, parametrized by degeneracy. To achieve this result, we modify the classic Bron–Kerbosch algorithm and show that it runs in time O(dn3 d/3). We also provide matching upper and lower bounds showing that the largest possible number of maximal cliques in an n-vertex graph with degeneracy d (when d is a multiple of 3 and n ≥ d + 3) is (n − d)3 d/3. Therefore, our algorithm matches the Θ(d(n − d)3 d/3) worst-case output size of the problem whenever n − d = Ω(n).

263 citations

Book ChapterDOI
14 Dec 1998
TL;DR: This talk will give several examples of breakthroughs derived through the application of the "discrepancy method," which raises the possibility that the deep mathematical techniques of discrepancy theory might be of utility to theoretical computer scientists.
Abstract: Discrepancy theory is the study of irregularities of distributions. A typical question is: given a "complicated" distribution, find a "simple" one that approximates it well. As it turns out, many questions in complexity theory can be reduced to problems of that type. This raises the possibility that the deep mathematical techniques of discrepancy theory might be of utility to theoretical computer scientists. As will be discussed in this talk this is, indeed, the case. We will give several examples of breakthroughs derived through the application of the "discrepancy method."

221 citations

Book ChapterDOI
10 Feb 2010
TL;DR: This paper proposes new approximate coloring and other related techniques which markedly improve the run time of the branch-and-bound algorithm MCR, previously shown to be the fastest maximum-clique-finding algorithm for a large number of graphs.
Abstract: This paper proposes new approximate coloring and other related techniques which markedly improve the run time of the branch-and-bound algorithm MCR (J. Global Optim., 37, 95–111, 2007), previously shown to be the fastest maximum-clique-finding algorithm for a large number of graphs. The algorithm obtained by introducing these new techniques in MCR is named MCS. It is shown that MCS is successful in reducing the search space quite efficiently with low overhead. Consequently, it is shown by extensive computational experiments that MCS is remarkably faster than MCR and other existing algorithms. It is faster than the other algorithms by an order of magnitude for several graphs. In particular, it is faster than MCR for difficult graphs of very high density and for very large and sparse graphs, even though MCS is not designed for any particular type of graphs. MCS can be faster than MCR by a factor of more than 100,000 for some extremely dense random graphs.

178 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
20234
202266
202110
202057
201981
201886