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The papers in this volume were selected for presentation at the
Eleventh Annual International Symposium on Algorithms and
Computation (ISAAC 2000), held on 18{20 December, 2000 at the
Institute of Information Science, Academia Sinica, Taipei, Taiwan.
Previous meetings were held in Tokyo (1990), Taipei (1991), Nagoya
(1992), Hong Kong (1993), Beijing (1994), Cairns (1995), Osaka
(1996), Singapore (1997), Taejon (1998), and Chennai (1999).
Submissions to the conference this year were conducted entirely
electro- cally. Thanks to the excellent software developed by the
Institute of Information Science, Academia Sinica, we were able to
carry out virtually all communication via the World Wide Web. In
response to the call for papers, a total of 87 extended abstracts
were submitted from 25 countries. Each submitted paper was handled
by at least three program committee members, with the assistance of
a number of external reviewers, as indicated by the referee list
found in the proceedings. There were many more acceptable papers
than there was space available in the symposium program, which made
the program committee's task extremely di cult. Finally 46 papers
were selected for presentation at the Symposium. In addition to
these contributed papers, the conference also included two invited
presentations by Dr. Jean-Daniel Boissonnat, INRIA
Sophia-Antipolis, France and Professor Jin-Yi Cai, University of
Wisconsin at Madison, Wisconsin, USA. It is expected that most of
the accepted papers will appear in a more complete form in scienti
c journals.
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Solving Irregularly Structured Problems in Parallel - 5th International Symosium, IRREGULAR'98, Berkeley, California, USA, August 9-11, 1998. Proceedings (Paperback, 1998 ed.)
Afonso Ferreira, Jose Rolim, Horst Simon, Shang-Hua Teng
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R1,762
Discovery Miles 17 620
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 5th
International Symposium on Solving Irregularly Structured Problems
in Parallel, IRREGULAR'98, held in Berkeley, California, in August
1998.
The 26 revised full papers presented were carefully reviewed and
selected for inclusion from several dozen submissions. Also
included are abstracts of four invited talks and 6 invited
presentations given during minisymposia held in parallel. The book
presents a unique overview on algorithmic, applicational, and
systems aspects arising in the development of efficient parallel
solutions to irregularly structured problems.
In the age of Big Data, efficient algorithms are in higher demand
more than ever before. While Big Data takes us into the asymptotic
world envisioned by our pioneers, it also challenges the classical
notion of efficient algorithms: algorithms that used to be
considered efficient, according to polynomial-time
characterization, may no longer be adequate for solving today's
problems. It is not just desirable but essential that efficient
algorithms should be scalable. In other words, their complexity
should be nearly linear or sub-linear with respect to the problem
size. Thus, scalability, not just polynomial-time computability,
should be elevated as the central complexity notion for
characterizing efficient computation. Scalable Algorithms for Data
and Network Analysis surveys a family of algorithmic techniques for
the design of scalable algorithms. These techniques include local
network exploration, advanced sampling, sparsification, and
geometric partitioning. They also include spectral
graph-theoretical methods, such as are used for computing
electrical flows and sampling from Gaussian Markov random fields.
These methods exemplify the fusion of combinatorial, numerical, and
statistical thinking in network analysis. This book illustrates the
use of these techniques by a few basic problems that are
fundamental in analyzing network data, particularly for the
identification of significant nodes and coherent
clusters/communities in social and information networks. It also
discusses some frameworks beyond graph-theoretical models for
studying conceptual questions that arise in network analysis and
social influences.
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