Randomized Algorithms

Author: Rajeev Motwani,Prabhakar Raghavan

Publisher: Cambridge University Press

ISBN: 9780521474658

Category: Computers

Page: 476

View: 3023

For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic concepts in the design and analysis of randomized algorithms. The first part of the text presents basic tools such as probability theory and probabilistic analysis that are frequently used in algorithmic applications. Algorithmic examples are also given to illustrate the use of each tool in a concrete setting. In the second part of the book, each chapter focuses on an important area to which randomized algorithms can be applied, providing a comprehensive and representative selection of the algorithms that might be used in each of these areas. Although written primarily as a text for advanced undergraduates and graduate students, this book should also prove invaluable as a reference for professionals and researchers.

Randomized Algorithms: Approximation, Generation, and Counting

Author: Russ Bubley

Publisher: Springer Science & Business Media

ISBN: 1447106954

Category: Computers

Page: 152

View: 4961

Randomized Algorithms discusses two problems of fine pedigree: counting and generation, both of which are of fundamental importance to discrete mathematics and probability. When asking questions like "How many are there?" and "What does it look like on average?" of families of combinatorial structures, answers are often difficult to find -- we can be blocked by seemingly intractable algorithms. Randomized Algorithms shows how to get around the problem of intractability with the Markov chain Monte Carlo method, as well as highlighting the method's natural limits. It uses the technique of coupling before introducing "path coupling" a new technique which radically simplifies and improves upon previous methods in the area.

Randomized Algorithms for Analysis and Control of Uncertain Systems

Author: Roberto Tempo,Giuseppe Calafiore,Fabrizio Dabbene

Publisher: Springer Science & Business Media

ISBN: 1846280524

Category: Computers

Page: 344

View: 9696

Moving on from earlier stochastic and robust control paradigms, this book introduces the fundamentals of probabilistic methods in the analysis and design of uncertain systems. The use of randomized algorithms, guarantees a reduction in the computational complexity of classical robust control algorithms and in the conservativeness of methods like H-infinity control. Features: • self-contained treatment explaining randomized algorithms from their genesis in the principles of probability theory to their use for robust analysis and controller synthesis; • comprehensive treatment of sample generation, including consideration of the difficulties involved in obtaining independent and identically distributed samples; • applications in congestion control of high-speed communications networks and the stability of quantized sampled-data systems. This monograph will be of interest to theorists concerned with robust and optimal control techniques and to all control engineers dealing with system uncertainties.

Probability and Computing

Randomized Algorithms and Probabilistic Analysis

Author: Michael Mitzenmacher,Eli Upfal

Publisher: Cambridge University Press

ISBN: 9780521835404

Category: Computers

Page: 352

View: 6529

Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols.Assuming only an elementary background in discrete mathematics, this textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses, including random sampling, expectations, Markov's and Chevyshev's inequalities, Chernoff bounds, balls and bins models, the probabilistic method, Markov chains, MCMC, martingales, entropy, and other topics.

Design and Analysis of Randomized Algorithms

Introduction to Design Paradigms

Author: J. Hromkovic

Publisher: Springer Science & Business Media

ISBN: 3540279032

Category: Computers

Page: 277

View: 1602

Systematically teaches key paradigmic algorithm design methods Provides a deep insight into randomization

Randomized Algorithms in Automatic Control and Data Mining

Author: Oleg Granichin,Zeev (Vladimir) Volkovich,Dvora Toledano-Kitai

Publisher: Springer

ISBN: 3642547869

Category: Computers

Page: 251

View: 2990

In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues. The book Randomized Algorithms in Automatic Control and Data Mining introduces the readers to the fundamentals of randomized algorithm applications in data mining (especially clustering) and in automatic control synthesis. The methods proposed in this book guarantee that the computational complexity of classical algorithms and the conservativeness of standard robust control techniques will be reduced. It is shown that when a problem requires "brute force" in selecting among options, algorithms based on random selection of alternatives offer good results with certain probability for a restricted time and significantly reduce the volume of operations.

Concentration of Measure for the Analysis of Randomized Algorithms

Author: Devdatt P. Dubhashi,Alessandro Panconesi

Publisher: Cambridge University Press

ISBN: 1139480995

Category: Computers

Page: N.A

View: 6034

Randomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms. It covers the basic toolkit from the Chernoff–Hoeffding bounds to more sophisticated techniques like martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as Chernoff–Hoeffding bounds in dependent settings. The authors emphasise comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus making the book accessible to computer scientists as well as probabilists and discrete mathematicians.

Computational Geometry

An Introduction Through Randomized Algorithms

Author: Ketan Mulmuley

Publisher: Prentice Hall


Category: Computers

Page: 447

View: 1263

This introduction to computational geometry is designed for beginners. It emphasizes simple randomized methods, developing basic principles with the help of planar applications, beginning with deterministic algorithms and shifting to randomized algorithms as the problems become more complex. It also explores higher dimensional advanced applications and provides exercises.

Primality Testing in Polynomial Time

From Randomized Algorithms to "PRIMES Is in P"

Author: Martin Dietzfelbinger

Publisher: Springer Science & Business Media

ISBN: 3540403442

Category: Mathematics

Page: 150

View: 7442

A self-contained treatment of theoretically and practically important efficient algorithms for the primality problem. The text covers the randomized algorithms by Solovay-Strassen and Miller-Rabin from the late 1970s as well as the recent deterministic algorithm of Agrawal, Kayal and Saxena. The volume is written for students of computer science, in particular those with a special interest in cryptology, and students of mathematics, and it may be used as a supplement for courses or for self-study.

An Introduction to Bioinformatics Algorithms

Author: Neil C. Jones,Pavel A. Pevzner,Pavel Pevzner

Publisher: MIT Press

ISBN: 9780262101066

Category: Computers

Page: 435

View: 3404

Algorithms and Complexity. Molecular Biology Primer. Exhaustive Search. Greedy Algorithms. Dynamic Programming Algorithms. Divide-and-Conquer Algorithms. Graph Algorithms. Combinatorial Pattern Matching. Clustering and Trees. Hidden Markov Models. Randomized Algorithms.

Handbook of Randomized Computing

Author: Sanguthevar Rajasekaran

Publisher: Springer Science & Business Media

ISBN: 9780792369585

Category: Computers

Page: 941

View: 9669

Introduction To Algorithms

Author: Thomas H.. Cormen,Thomas H Cormen,Charles E Leiserson,Ronald L Rivest,Clifford Stein

Publisher: MIT Press

ISBN: 9780262032933

Category: Computers

Page: 1180

View: 4349

An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms.

Complexity and Approximation

Combinatorial Optimization Problems and Their Approximability Properties

Author: Giorgio Ausiello,Pierluigi Crescenzi,Giorgio Gambosi,Viggo Kann,Alberto Marchetti-Spaccamela,Marco Protasi

Publisher: Springer Science & Business Media

ISBN: 9783540654315

Category: Business & Economics

Page: 524

View: 918

This book documents the state of the art in combinatorial optimization, presenting approximate solutions of virtually all relevant classes of NP-hard optimization problems. The wealth of problems, algorithms, results, and techniques make it an indispensible source of reference for professionals. The text smoothly integrates numerous illustrations, examples, and exercises.

Constraint and Integer Programming

Toward a Unified Methodology

Author: Michela Milano

Publisher: Springer Science & Business Media

ISBN: 9781402075834

Category: Computers

Page: 370

View: 5261

Constraint and Integer Programming presents some of the basic ideas of constraint programming and mathematical programming, explores approaches to integration, brings us up to date on heuristic methods, and attempts to discern future directions in this fast-moving field.

Stochastic Algorithms: Foundations and Applications

International Symposium, SAGA 2001 Berlin, Germany, December 13-14, 2001 Proceedings

Author: Kathleen Steinhöfel

Publisher: Springer

ISBN: 3540453229

Category: Mathematics

Page: 208

View: 7963

SAGA 2001, the ?rst Symposium on Stochastic Algorithms, Foundations and Applications, took place on December 13–14, 2001 in Berlin, Germany. The present volume comprises contributed papers and four invited talks that were included in the ?nal program of the symposium. Stochastic algorithms constitute a general approach to ?nding approximate solutions to a wide variety of problems. Although there is no formal proof that stochastic algorithms perform better than deterministic ones, there is evidence by empirical observations that stochastic algorithms produce for a broad range of applications near-optimal solutions in a reasonable run-time. The symposium aims to provide a forum for presentation of original research in the design and analysis, experimental evaluation, and real-world application of stochastic algorithms. It focuses, in particular, on new algorithmic ideas invo- ing stochastic decisions and exploiting probabilistic properties of the underlying problem domain. The program of the symposium re?ects the e?ort to promote cooperation among practitioners and theoreticians and among algorithmic and complexity researchers of the ?eld. In this context, we would like to express our special gratitude to DaimlerChrysler AG for supporting SAGA 2001. The contributed papers included in the proceedings present results in the following areas: Network and distributed algorithms; local search methods for combinatorial optimization with application to constraint satisfaction problems, manufacturing systems, motor control unit calibration, and packing ?exible - jects; and computational learning theory.

Computer Science Handbook, Second Edition

Author: Allen B. Tucker

Publisher: CRC Press

ISBN: 0203494458

Category: Computers

Page: 2752

View: 8000

When you think about how far and fast computer science has progressed in recent years, it's not hard to conclude that a seven-year old handbook may fall a little short of the kind of reference today's computer scientists, software engineers, and IT professionals need. With a broadened scope, more emphasis on applied computing, and more than 70 chapters either new or significantly revised, the Computer Science Handbook, Second Edition is exactly the kind of reference you need. This rich collection of theory and practice fully characterizes the current state of the field and conveys the modern spirit, accomplishments, and direction of computer science. Highlights of the Second Edition: Coverage that reaches across all 11 subject areas of the discipline as defined in Computing Curricula 2001, now the standard taxonomy More than 70 chapters revised or replaced Emphasis on a more practical/applied approach to IT topics such as information management, net-centric computing, and human computer interaction More than 150 contributing authors--all recognized experts in their respective specialties New chapters on: cryptography computational chemistry computational astrophysics human-centered software development cognitive modeling transaction processing data compression scripting languages event-driven programming software architecture

Randomized Algorithms for Matrices and Data

Author: Michael W. Mahoney

Publisher: N.A

ISBN: 9781601985064

Category: Computers

Page: 114

View: 6073

Randomized Algorithms for Matrices and Data provides a detailed overview, appropriate for both students and researchers from all of these areas, of recent work on the theory of randomized matrix algorithms as well as the application of those ideas to the solution of practical problems in large-scale data analysis