Graph partitioning and graph clustering: 10th DIMACS Implementation Challenge Workshop, Fe…
by Bader, David A., Sanders, Peter, Meyerhenke, Henning, DIMACS Implementation Challenge Workshop, Georgia Institute of Technology, Atlanta, GA)
fromContemporary mathematics - American Mathematical Society (P…
"Graph partitioning and graph clustering are ubiquitous subtasks in many applications where graphs play an important role. Generally speaking, both techniques aim at the identification of vertex subsets with many internal and few external edges. To name only a few, problems addr…
"Graph partitioning and graph clustering are ubiquitous subtasks in many applications where graphs play an important role. Generally speaking, both techniques aim at the identification of vertex subsets with many internal and few external edges. To name only a few, problems addr…
This book sheds light on state-of-the-art theories for more challenging outfit compatibility modeling scenarios. In particular, this book presents several cutting-edge graph learning techniques that can be used for outfit compatibility modeling. Due to its remarkable economic va…
This comprehensive text on the theory and techniques of graph neural networks takes students, practitioners, and researchers from the basics to the state of the art. It systematically introduces foundational topics such as filtering pooling, robustness, and scalability and then …
Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the …
Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the …
"Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, like approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computat…
Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, like approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computati…
Introduction -- Graph theory and concepts -- Graph platforms and processing -- Pathfinding and graph search algorithms -- Centrality algorithms -- Community detection algorithms -- Graph algorithms in practice -- Using graph algorithms to enhance machine learning. Learn how gra…
This book constitutes selected papers presented at the 5th International Workshop on Software Foundations for Data Interoperability, SFDI 2021, held in Copenhagen, Denmark, in August 2021. The 4 full papers and one short paper were thorougly reviewed and selected from 8 submissi…
"Algorithmic graph theory has been expanding at an extremely rapid rate since the middle of the twentieth century, in parallel with the growth of computer science and the accompanying utilization of computers, where efficient algorithms have been a prime goal. This book presents…