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The First International Symposium on Combinatorics, Algorithms, Probabilistic and Experimental Methodologies was held in Hangzhou, China, in April 2007. The symposium provided an interdisciplinary forum for researchers to share their discoveries and approaches; search for ideas, methodologies, and tool boxes; find better, faster, and more accurate solutions; and develop a research agenda of common interest. This volume constitutes the refereed post-proceedings of the symposium. Inside you'll find 46 full papers. They represent some of the most important thinking and advancements in the field. The papers address large data processing problems using different methodologies from major disciplines such as computer science, combinatorics, and statistics.
The conference proceeding LNCS 11346 constitutes the refereed proceedings of the 12th International Conference on Combinatorial Optimization and Applications, COCOA 2018, held in Atlanta, GA, USA, in December 2018. The 50 full papers presented were carefully reviewed and selected from 106 submissions. The papers cover most aspects of t graph algorithms, routing and network design problems, scheduling algorithms, network optimization, combinatorial algorithms, approximation algorithms, paths and connectivity problems and much more.
Running to almost 400 pages, and featuring more than 40 papers, this work on combinatorial optimization and applications will be seen as an important addition to the literature. It constitutes the refereed proceedings of the first International Conference on Combinatorial Optimization and Applications, COCOA 2007, held in Xi'an, China in August of that year. The 29 revised full papers presented together with 8 invited papers and 2 invited presentations were carefully reviewed and selected from 114 submissions and cover both theoretical issues and practical applications.
Praise for the Third Edition “Researchers of any kind of extremal combinatorics or theoretical computer science will welcome the new edition of this book.” - MAA Reviews Maintaining a standard of excellence that establishes The Probabilistic Method as the leading reference on probabilistic methods in combinatorics, the Fourth Edition continues to feature a clear writing style, illustrative examples, and illuminating exercises. The new edition includes numerous updates to reflect the most recent developments and advances in discrete mathematics and the connections to other areas in mathematics, theoretical computer science, and statistical physics. Emphasizing the methodology and techniques that enable problem-solving, The Probabilistic Method, Fourth Edition begins with a description of tools applied to probabilistic arguments, including basic techniques that use expectation and variance as well as the more advanced applications of martingales and correlation inequalities. The authors explore where probabilistic techniques have been applied successfully and also examine topical coverage such as discrepancy and random graphs, circuit complexity, computational geometry, and derandomization of randomized algorithms. Written by two well-known authorities in the field, the Fourth Edition features: Additional exercises throughout with hints and solutions to select problems in an appendix to help readers obtain a deeper understanding of the best methods and techniques New coverage on topics such as the Local Lemma, Six Standard Deviations result in Discrepancy Theory, Property B, and graph limits Updated sections to reflect major developments on the newest topics, discussions of the hypergraph container method, and many new references and improved results The Probabilistic Method, Fourth Edition is an ideal textbook for upper-undergraduate and graduate-level students majoring in mathematics, computer science, operations research, and statistics. The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and Academia Europaea. A coeditor of the journal Random Structures and Algorithms, Dr. Alon is the recipient of the Polya Prize, The Gödel Prize, The Israel Prize, and the EMET Prize. Joel H. Spencer, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is a Sloane Foundation Fellow. Dr. Spencer has written more than 200 published articles and is the coauthor of Ramsey Theory, Second Edition, also published by Wiley.
The refereed proceedings of the 14th Annual International Computing and Combinatorics Conference, COCOON 2008, held in Dalian, China, in June 2008. The 66 revised full papers presented were carefully reviewed and selected from 172 submissions. The papers are organized in topical sections on algorithms and data structures, algorithmic game theory and online algorithms, automata, languages, logic, and computability, combinatorics related to algorithms and complexity, complexity theory, cryptography, reliability and security, and database theory, computational biology and bioinformatics, computational algebra, geometry, and number theory, graph drawing and information visualization, graph theory and algorithms, communication networks, and optimization, wireless network, network optimization, and scheduling problem.
This books reviews recent theoretical and practical advances on suffix sorting and introduces algorithmic solutions to problems of wide interest for the construction of fundamental data structures that operate efficiently on strings namely, constructing the suffix array, the longest common prefix (LCP) array, the document array and the Lyndon array. These data structures are the cornerstone of many algorithmic solutions in Bioiformatics, Information Retrieval and Data Compression. This book introduces the relevant problem areas, their importance, the notation and related algorithms and then presents the algorithmic solutions for indexing data structure constructions. This book is intended for graduate students, researchers and practitioners from Computer Science and Bioinformatics with a strong interest in algorithmic aspects.
This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.
This comprehensive compendium provides a rigorous framework to tackle the daunting challenges of designing correct and efficient algorithms. It gives a uniform approach to the design, analysis, optimization, and verification of algorithms. The volume also provides essential tools to understand algorithms and their associated data structures.This useful reference text describes a way of thinking that eases the task of proving algorithm correctness. Working through a proof of correctness reveals an algorithm's subtleties in a way that a typical description does not. Algorithm analysis is presented using careful definitions that make the analyses mathematically rigorous.Related Link(s)
Leave nothing to chance. This cliche embodies the common belief that ran domness has no place in carefully planned methodologies, every step should be spelled out, each i dotted and each t crossed. In discrete mathematics at least, nothing could be further from the truth. Introducing random choices into algorithms can improve their performance. The application of proba bilistic tools has led to the resolution of combinatorial problems which had resisted attack for decades. The chapters in this volume explore and celebrate this fact. Our intention was to bring together, for the first time, accessible discus sions of the disparate ways in which probabilistic ideas are enriching discrete mathematics. These discussions are aimed at mathematicians with a good combinatorial background but require only a passing acquaintance with the basic definitions in probability (e.g. expected value, conditional probability). A reader who already has a firm grasp on the area will be interested in the original research, novel syntheses, and discussions of ongoing developments scattered throughout the book. Some of the most convincing demonstrations of the power of these tech niques are randomized algorithms for estimating quantities which are hard to compute exactly. One example is the randomized algorithm of Dyer, Frieze and Kannan for estimating the volume of a polyhedron. To illustrate these techniques, we consider a simple related problem. Suppose S is some region of the unit square defined by a system of polynomial inequalities: Pi (x. y) ~ o.
This book provides a comprehensive and up-to-date collection of review articles focusing on RNA-mediated regulation in prokaryotes. The various modes of action include the direct interaction with proteins, direct sensing of metabolites or of physical parameters, and the interaction with RNAs to stimulate or prevent binding of ribosomes or to stimulate degradation. Written by leading experts in the field, the book covers small RNA functions, RNA thermometers, riboswitches, the diversity of small RNA-guided CRISPR-Cas defense systems and selected RNA chaperons in both prokaryotic domains, bacteria and archaea. Recent advances towards the computational identification of regulatory RNAs and their targets are included and particular attention is paid to small RNA in pathogenic bacteria. This volume is the only one exclusively covering regulatory RNAs in the prokaryotic domains to date, making it essential literature for anyone interested in RNA function and gene regulation and a valuable resource for teaching these concepts.