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Efficient Graph Representations

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Efficient Graph Representations

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Author : Jeremy P. Spinrad
language : en
Publisher: American Mathematical Soc.
Release Date : 2003-01-01

Efficient Graph Representations written by Jeremy P. Spinrad and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-01 with Mathematics categories.

The book deals with questions which arise from storing a graph in a computer. Different classes of graphs admit different forms of computer representations, and focusing on the representations gives a new perspective on a number of problems. For a variety of classes of graphs, the book considers such questions as existence of good representations, algorithms for finding representations, questions of characterizations in terms of representation, and how the representation affects the complexity of optimization problems. General models of efficient computer representations are also considered. The book is designed to be used both as a text for a graduate course on topics related to graph representation, and as a monograph for anyone interested in research in the field of graph representation. The material is of interest both to those focusing purely on graph theory and to those working in the area of graph algorithms.

Efficient Graph Representations

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Author : Jeremy P. Spinrad
language : en
Publisher: American Mathematical Soc.
Release Date : 2003-01-01

Efficient Graph Representations

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Author : Jeremy P. Spinrad
language : en
Publisher: American Mathematical Soc.
Release Date : 2003-01-01

Graph Representation Learning

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Author : William L. Hamilton
language : en
Publisher: Springer Nature
Release Date : 2022-06-01

Graph Representation Learning written by William L. Hamilton and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.

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.

Semi Supervised Learning

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Author : Olivier Chapelle
language : en
Publisher: MIT Press
Release Date : 2010-01-22

Semi Supervised Learning written by Olivier Chapelle and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-22 with Computers categories.

A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems: state-of-the-art algorithms, a taxonomy of the field, applications, benchmark experiments, and directions for future research. In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in which all training examples are labeled) and unsupervised learning (in which no label data are given). Interest in SSL has increased in recent years, particularly because of application domains in which unlabeled data are plentiful, such as images, text, and bioinformatics. This first comprehensive overview of SSL presents state-of-the-art algorithms, a taxonomy of the field, selected applications, benchmark experiments, and perspectives on ongoing and future research.Semi-Supervised Learning first presents the key assumptions and ideas underlying the field: smoothness, cluster or low-density separation, manifold structure, and transduction. The core of the book is the presentation of SSL methods, organized according to algorithmic strategies. After an examination of generative models, the book describes algorithms that implement the low-density separation assumption, graph-based methods, and algorithms that perform two-step learning. The book then discusses SSL applications and offers guidelines for SSL practitioners by analyzing the results of extensive benchmark experiments. Finally, the book looks at interesting directions for SSL research. The book closes with a discussion of the relationship between semi-supervised learning and transduction.

Advanced Graph Theory

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Author : Dr. Sriraj M. A.
language : en
Publisher: RK Publication
Release Date : 2024-12-12

Advanced Graph Theory written by Dr. Sriraj M. A. and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-12 with Computers categories.

Advanced Graph Theory is mathematical foundations, algorithms, and applications of graph theory. Topics such as connectivity, coloring, network flows, and spectral graph theory, this both classical and modern developments. It provides rigorous proofs, real-world applications, and advanced techniques used in computer science, optimization, and combinatorial mathematics. Suitable for researchers, graduate students, and professionals, the balances theoretical depth with practical insights, making it an essential resource for those seeking a deeper understanding of graph structures and their complexities.

C Data Structures Explained A Practical Guide With Examples

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Author : William E. Clark
language : en
Publisher: Walzone Press
Release Date : 2025-03-30

C Data Structures Explained A Practical Guide With Examples written by William E. Clark and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-30 with Computers categories.

"C++ Data Structures Explained: A Practical Guide with Examples" is a meticulously crafted resource designed for programmers and computer science enthusiasts eager to master data structures in C++. This guide comprehensively walks readers through crucial elements of the C++ language, cultivating a solid foundation for understanding and implementing data structures seamlessly in real-world applications. Each chapter delves into both fundamental and advanced topics, ensuring a well-rounded grasp of the principles underlying efficient data management. The book is structured to provide an in-depth exploration of various data structures, starting from basic arrays and strings to complex graphs and hierarchical tree models. Readers will gain valuable insights into dynamic memory allocation with linked lists, and the orderly management of data via stacks and queues. Furthermore, the book offers a comprehensive look at optimization techniques using hash tables and heaps, integrating both theoretical knowledge and practical coding examples to facilitate applied learning. Intended for students, educators, and professionals within the field of computer science, this book emphasizes the practical application of data structures in C++ programming. Through a blend of conceptual discussions and detailed examples, readers are equipped not only to understand the mechanics of data structures but to apply them effectively in developing robust, efficient software solutions. The text's clear and precise approach ensures that readers are well-prepared to solve complex computational problems, shaping a confident approach to coding and algorithm development.

The Boost Graph Library

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Author : Jeremy G. Siek
language : en
Publisher: Pearson Education
Release Date : 2001-12-20

The Boost Graph Library written by Jeremy G. Siek and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-12-20 with Computers categories.

The Boost Graph Library (BGL) is the first C++ library to apply the principles of generic programming to the construction of the advanced data structures and algorithms used in graph computations. Problems in such diverse areas as Internet packet routing, molecular biology, scientific computing, and telephone network design can be solved by using graph theory. This book presents an in-depth description of the BGL and provides working examples designed to illustrate the application of BGL to these real-world problems. Written by the BGL developers, The Boost Graph Library: User Guide and Reference Manual gives you all the information you need to take advantage of this powerful new library. Part I is a complete user guide that begins by introducing graph concepts, terminology, and generic graph algorithms. This guide also takes the reader on a tour through the major features of the BGL; all motivated with example problems. Part II is a comprehensive reference manual that provides complete documentation of all BGL concepts, algorithms, and classes. Readers will find coverage of: Graph terminology and concepts Generic programming techniques in C++ Shortest-path algorithms for Internet routing Network planning problems using the minimum-spanning tree algorithms BGL algorithms with implicitly defined graphs BGL Interfaces to other graph libraries BGL concepts and algorithms BGL classes–graph, auxiliary, and adaptor Groundbreaking in its scope, this book offers the key to unlocking the power of the BGL for the C++ programmer looking to extend the reach of generic programming beyond the Standard Template Library.

Algorithmic Foundations For Social Advancement

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Author : Shin-ichi Minato
language : en
Publisher: Springer Nature
Release Date : 2025-03-07

Algorithmic Foundations For Social Advancement written by Shin-ichi Minato and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-07 with Computers categories.

This Open access book provides an overview of the cutting-edge research to systematize innovative foundations in algorithmic theories and techniques, and apply them to solve socially significant real-life problems, thereby driving social transformation and advancement. Formulating such social problems into well-defined mathematical or computational terms requires not only a solid theoretical foundation but also a deep understanding of the application domain itself. The content is divided into three parts. Following an introductory chapter in Part I, Part II discusses how to bridge the gap between algorithmic solutions and social advancement. Chapters 2, 3, and 4 present motivating problems that showcase the remarkable performance improvements driven by algorithmic technologies, followed by examples of how interfaces and tools were provided to apply these solutions to real-world challenges. The subsequent Chapters 5 through 12 then focus on interdisciplinary discussions regarding how to formulate real societal issues into a catalog of problems to be addressed. Finally, Part III, spanning Chapters 13 to 23, highlights selected topics on the innovative algorithmic foundations developed through the research project, focusing on intriguing subjects and the latest ongoing research. These include processing large-scale discrete structures, graph algorithms, discrete optimization, quantum algorithms, and various other topics related to algorithmic foundations. This book will serve as a valuable resource for readers interested in the use of algorithms in real-life problems. This book is based on the research project in Japan, Algorithmic Foundations for Social Advancement.

Graph Based Representations In Pattern Recognition

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Author : Xiaoyi Jiang
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-05-10

Graph Based Representations In Pattern Recognition written by Xiaoyi Jiang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-10 with Computers categories.

This book constitutes the refereed proceedings of the 8th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2011, held in Münster, Germany, in May 2011. The 34 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on graph-based representation and characterization, graph matching, classification, and querying, graph-based learning, graph-based segmentation, and applications.

Efficient Graph Representations

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