• Title: Graph Theory and Additive Combinatorics: Exploring Structure and Randomness
• Authors Yufei Zhao
• Publisher: Cambridge University Press (2023); eBook (Online Edition by MIT)
• Paperback: 338 pages
• eBook: PDF and PDF Files
• Language: English
• ISBN-10: 1009310941
• ISBN-13: 978-1009310949
• Share This:  

Book Description

An introductory text covering classical and modern developments in graph theory and additive combinatorics, based on Zhao's MIT course.

Using the dichotomy of structure and pseudorandomness as a central theme, this accessible text provides a modern introduction to extremal graph theory and additive combinatorics.

• Yufei Zhao is Associate Professor of Mathematics at the Massachusetts Institute of Technology.

• Amazon

• Graph Theory
• Combinatorics
• Discrete and Finite Mathematics

• Graph Theory and Additive Combinatorics: Exploring Structure and Randomness
• The Mirror Site (1) - Ziiped PDF and PDF Files

• An Introduction to Combinatorics and Graph Theory

  This book walks the reader through the classic parts of Combinatorics and graph theory, while also discussing some recent progress in the area: on the one hand, providing material that will help students learn the basic techniques.

• Graphs for Pattern Recognition: Systems of Linear Inequalities

  This book deals with mathematical constructions that are foundational in such an important area of Data Mining as Pattern Recognition. By using combinatorial and graph theoretic techniques, a closer look is taken at infeasible systems of linear inequalities.

• Spectral Geometry of Graphs (Pavel Kurasov)

  This open access book gives a systematic introduction into the Spectral Theory of differential operators on metric graphs. Main focus is on the fundamental relations between the spectrum and the geometry of the underlying graph.

• Groups as Graphs (W.B.Vasantha Kandasamy, et al.)

  Through this book, for the first time we represent every finite group in the form of a graph. The authors choose to call these graphs as identity graph, since the main role in obtaining the graph is played by the identity element of the group.

• Games on Graphs (Nathalie Bertrand, et al.)

  This book presents the state of the art on Games on Graphs, which is part of Game Theory. Games on graphs is the field concerned with games whose rules and evolution are represented by a graph.

• Graph Theory (Reinhard Diestel)

  This book covers the core material of the subject with concise yet reliably complete proofs, while offering glimpses of more advanced methods in each field by one or two deeper results, again with proofs given in full detail.

• Hypergraph Computation (Qionghai Dai, et al.)

  Comprehensive and systematic overview for Hypergraph computation. Rich blend of basic knowledge, theoretical analysis, algorithm introduction, and key applications. Describes hypergraph computation applications in computer vision, medical applications, etc.

• Deep Learning on Graphs (Yao Ma, et al)

  The book is a self-contained, comprehensive text on foundations and techniques of Graph Neural Networks with applications in NLP, data mining, vision and healthcare. Accessible to who want to use graph neural networks to advance their disciplines.

• Planar Maps, Random Walks and Circle Packing (Asaf Nachmias)

  This open access book focuses on the interplay between Random Walks on planar maps and Koebe’s circle packing theorem. Entirely self-contained. Many classical proofs have been simplified and streamlined. Contains numerous useful exercises.

• Random Walks and Electrical Networks (Peter G. Doyle, et al.)

  A popular account of the connection between Random Walks and electric networks. Electric networks is part of the much broader subject of general network theory which is itself a branch of the mathematical subject of graph theory.

• Digraphs: Theory, Algorithms and Applications (J. Bang-Jensen)

  This book is an essential, comprehensive reference of Digraphs covering the theoretical aspects of the subject, focus on applications which include quantum mechanics, bioinformatics, embedded computing, and the travelling salesman problem.

• Graph Theory - Advanced Algorithms and Applications

  Not only will the methods and explanations help you to understand more about graph theory, but you will find it joyful to discover ways that you can apply graph theory in your applications or scientific research.

• Graph Theory and Complex Networks (Maarten van Steen)

  This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. It also aims to provide an introduction to the modern field of network science.