Download or read book Matching Extensions in the Powers of Graphs written by Kara Lee Walcher and published by . This book was released on 1995 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Graph Factors and Matching Extensions written by Qinglin Roger Yu and published by Springer. This book was released on 2011-09-18 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Graph Factors and Matching Extensions" deals with two important branches of graph theory – factor theory and extendable graphs. Due to the mature techniques and wide ranges of applications, factors and matchings become useful tools in investigation of many theoretical problems and practical issues. This book includes basic techniques, theoretical foundations, as well as recent advances in the field. It also discusses open problems and conjectures to inspire the readers. This book is primarily aimed at researchers and graduate students in graph theory and combinatorics in general. However, all the necessary prerequisites are developed from scratch and should be accessible to upper-level undergraduate students with prior knowledge of graph theory. Dr. Yu is a professor in the Department of Mathematics and Statistics at the Thompson Rivers University of Canada. His research interests include graph theory and combinatorial optimization. Dr. Liu is a professor in the School of Mathematics at Shandong University of China. Her research interests include graph theory and matroid theory.

Download or read book Congressus Numerantium written by and published by . This book was released on 1970 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Graph Theoretic Concepts in Computer Science written by Rolf H. Möhring and published by Springer Science & Business Media. This book was released on 1997-10-29 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the carefully refereed post-proceedings of the 22nd International Workshop on Graph-Theoretic Concepts in Computer Science, WG '96, held in Cadenabbia, Italy, in June 1996. The 30 revised full papers presented in the volume were selected from a total of 65 submissions. This collection documents the state of the art in the area. Among the topics addressed are graph algorithms, graph rewriting, hypergraphs, graph drawing, networking, approximation and optimization, trees, graph computation, and others.

Download or read book Matching Extensions in Regular Graphs with Small Diameter written by Ivana Koroman and published by . This book was released on 2019 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book American Doctoral Dissertations written by and published by . This book was released on 2000 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Graphs that are Critical with Respect to Matching Extension and Diameter written by Nawarat Ananchuen and published by . This book was released on 1994 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: We also establish that a k-extendable graph G of order 2n has k + 1 /= delta(G)

Download or read book Matching Extension and the Genus of a Graph written by Michael D. Plummer and published by . This book was released on 1986 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Let G be a graph with p points having a perfect matching and suppose n is a positive integer with n

Download or read book Mathematical Reviews written by and published by . This book was released on 2002 with total page 1092 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Matching Extension and Connectivity in Graphs 1 Introduction and Terminology written by M. D. Plummer and published by . This book was released on 1986 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introduction to Random Graphs written by Alan Frieze and published by Cambridge University Press. This book was released on 2016 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.

Download or read book Theory and Applications of Models of Computation written by Jan Kratochvil and published by Springer Science & Business Media. This book was released on 2010-05-20 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Theory and Applications of Models of Computation, TAMC 2010, held in Prague, Czech Republic, in June 2010. The 35 revised full papers presented together with 5 contributions of special sessions as well as 2 plenary talks were carefully reviewed and selected from 76 submissions. The papers address the three main themes of the conference which were computability, complexity, and algorithms and present current research in these fields with aspects to theoretical computer science, algorithmic mathematics, and applications to the physical sciences.

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2002 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Download or read book Algorithmic Graph Theory written by James A. McHugh and published by . This book was released on 1990 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Graph theoretic Concepts in Computer Science written by and published by . This book was released on 1997 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Perspectives of Neural Symbolic Integration written by Barbara Hammer and published by Springer. This book was released on 2007-08-14 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: When it comes to robotics and bioinformatics, the Holy Grail everyone is seeking is how to dovetail logic-based inference and statistical machine learning. This volume offers some possible solutions to this eternal problem. Edited with flair and sensitivity by Hammer and Hitzler, the book contains state-of-the-art contributions in neural-symbolic integration, covering `loose' coupling by means of structure kernels or recursive models as well as `strong' coupling of logic and neural networks.