|
Showing 1 - 3 of
3 matches in All Departments
Computational Complexity of Counting and Sampling provides readers
with comprehensive and detailed coverage of the subject of
computational complexity. It is primarily geared toward researchers
in enumerative combinatorics, discrete mathematics, and theoretical
computer science. The book covers the following topics: Counting
and sampling problems that are solvable in polynomial running time,
including holographic algorithms; #P-complete counting problems;
and approximation algorithms for counting and sampling. First, it
opens with the basics, such as the theoretical computer science
background and dynamic programming algorithms. Later, the book
expands its scope to focus on advanced topics, like stochastic
approximations of counting discrete mathematical objects and
holographic algorithms. After finishing the book, readers will
agree that the subject is well covered, as the book starts with the
basics and gradually explores the more complex aspects of the
topic. Features: Each chapter includes exercises and solutions
Ideally written for researchers and scientists Covers all aspects
of the topic, beginning with a solid introduction, before shifting
to computational complexity's more advanced features, with a focus
on counting and sampling
Computational Complexity of Counting and Sampling provides readers
with comprehensive and detailed coverage of the subject of
computational complexity. It is primarily geared toward researchers
in enumerative combinatorics, discrete mathematics, and theoretical
computer science. The book covers the following topics: Counting
and sampling problems that are solvable in polynomial running time,
including holographic algorithms; #P-complete counting problems;
and approximation algorithms for counting and sampling. First, it
opens with the basics, such as the theoretical computer science
background and dynamic programming algorithms. Later, the book
expands its scope to focus on advanced topics, like stochastic
approximations of counting discrete mathematical objects and
holographic algorithms. After finishing the book, readers will
agree that the subject is well covered, as the book starts with the
basics and gradually explores the more complex aspects of the
topic. Features: Each chapter includes exercises and solutions
Ideally written for researchers and scientists Covers all aspects
of the topic, beginning with a solid introduction, before shifting
to computational complexity's more advanced features, with a focus
on counting and sampling
As genome-sequencing costs continue their downward spiral,
sequencing of closely related organisms has become increasingly
a?ordable. The growing amount of genomic data available demands for
the constant development of computational tools to be applied in
comparative genomics. The RECOMB Workshop on C- parative Genomics
(RECOMB-CG) is devoted to bringing together scientists working on
all aspects of comparative genomics, from computer scientists, ma-
ematicians and statisticians working on novel computational
approaches for genome analysis and comparison, to biologists
applying these computational tools to study the structure and the
evolution of prokaryotic and eukaryotic genomes. This volume
contains the 19 papers presented at the 7th Annual RECOMB-CG
workshop held during September 27-29, 2009 at the Renyi Institute,
in Budapest, Hungary. The papers published in these proceedings
were selected for oral p- sentation from 31 submissions from
scientists around the world. Each paper was reviewed by at least
three members of the Program Committee in a stringent and
thoughtful peer-review process.
|
|