Description
Book SynopsisCommunication complexity is the mathematical study of scenarios where several parties need to communicate to achieve a common goal. This tutorial text explains fundamentals and recent developments in an accessible and illustrated form, including applications in circuit complexity, proof complexity, streaming algorithms and distributed computing.
Trade Review'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
Table of ContentsPreface; 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.
