Communication complexity is the mathematical study of scenarios where several parties need to communicate to achieve a common goal, a situation that naturally appears during computation. This introduction presents the most recent developments in an accessible form, providing the language to unify several disjoint research subareas. Written as a guide for a graduate course on communication complexity, it will interest a broad audience in computer science, from advanced undergraduates to researchers in areas ranging from theory to algorithm design to distributed computing. The first part presents basic theory in a clear and illustrative way, offering beginners an entry into the field. The second part describes applications including circuit complexity, proof complexity, streaming algorithms, extension complexity of polytopes, and distributed computing. Proofs throughout the text use ideas from a wide range of mathematics, including geometry, algebra, and probability. Each chapter contains numerous examples, figures, and exercises to aid understanding.
Rezensionen / Stimmen
'This looks like an essential resource for any student who wants to understand deterministic and randomized communication complexity deeply.' Scott Aaronson, University of Texas 'Communication complexity is not only a beautiful and important area of the theory of computing, it is also vibrant and ever-changing. Two of the leading researchers in this area take us through a fascinating journey into the theory and applications of communication complexity and through old and new jams. I feel inspired to teach a course based on this book and help spread the word.' Omer Reingold, Stanford University, California 'This book is a much-needed introductory text on communication complexity. It will bring the reader up to speed on both classical and more recent lower bound techniques, and on key application areas. An invaluable resource for anyone interested in complexity theory.' Mark Braverman, Princeton University, New Jersey '... a great book ... relevant to advanced undergrads and graduate students alike, while the more advanced topics will also be of interest to researchers ...' Michael Cadilhac, SIGACT News Book review column '... must-have reference for students but will be welcomed by researchers as well because it is so well-written and aptly organized ... Highly recommended.' A. Misseldine, CHOICE
Sprache
Verlagsort
Zielgruppe
Produkt-Hinweis
Fadenheftung
Gewebe-Einband
Illustrationen
Worked examples or Exercises; 10 Halftones, black and white; 74 Line drawings, black and white
Maße
Höhe: 256 mm
Breite: 180 mm
Dicke: 20 mm
Gewicht
ISBN-13
978-1-108-49798-5 (9781108497985)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Anup Rao is an Associate Professor at the School of Computer Science, University of Washington. He received his Ph.D. in Computer Science from the University of Texas, Austin, and was a researcher at the Institute for Advanced Study, Princeton. His research interests are primarily in theoretical computer science. Amir Yehudayoff is Associate Professor of Mathematics at Technion - Israel Institute of Technology, Haifa. He is interested in mathematical questions that are motivated by theoretical computer science and machine learning. He was a member of the Institute for Advanced Study in Princeton, and served as the secretary of the Israel Mathematical Union. He has won several prizes, including the Cooper Prize and the Krill Prize for excellence in scientific research, and the Kurt Mahler Prize for excellence in mathematics.
Autor*in
University of Washington
Technion - Israel Institute of Technology, Haifa
Preface; Conventions and preliminaries; Introduction; Part I. Communication: 1. Deterministic protocols; 2. Rank; 3. Randomized protocols; 4. Numbers on foreheads; 5. Discrepancy; 6. Information; 7. Compressing communication; 8. Lifting; Part II. Applications: 9. Circuits and proofs; 10. Memory size; 11. Data structures; 12. Extension Complexity of Polytopes; 13. Distributed computing.
