Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation …
Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to public-key …
Build machine learning algorithms using graph data and efficiently exploit topological information within your modelsKey FeaturesImplement machine learning techniques and …
Practical methods for analyzing your data with graphs, revealing hidden connections and new insights. Graphs are the natural way to …
This book is Part II of the fourth edition of Robert Sedgewick and Kevin Wayne's Algorithms, the leading textbook on …
Data is everywhere - it's just not very well connected, which makes it super hard to relate dataset to dataset. …
At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations …
Advanced Data Structures presents a comprehensive look at the ideas, analysis, and implementation details of data structures as a specialized …
A modern treatment of data structures using the C programming language. Emphasizes such programming practices as dynamic memory allocation, recursion, …
Algorithmic Graph Theory and Perfect Graphs, first published in 1980, has become the classic introduction to the field. This new …
The book has many important features which make it suitable for both undergraduate and postgraduate students in various branches of …
Content: Chapter 1 Basic Concepts (pages 21–43): Chapter 2 Trees (pages 45–69): Chapter 3 Colorings (pages 71–82): Chapter 4 Directed …
Издательство North-Holland, 1982, -271 pp.Graph theory is increasingly being used to model situations arising in the applied sciences. This text, …
This book provides an extensive set of tools for applying fuzzy mathematics and graph theory to real-life problems. Balancing the …
Confusing Textbooks? Missed Lectures? Tough Test Questions? Fortunately for you, there's Schaum's Outlines. More than 40 million students have trusted …
Graph Theory and Its Applications, Third Edition is the latest edition of the international, bestselling textbook for undergraduate courses in …
A lively invitation to the flavor, elegance, and power of graph theoryThis mathematically rigorous introduction is tempered and enlivened by …
This textbook can serve as a comprehensive manual of discrete mathematics and graph theory for non-Computer Science majors; as a …
Covering a wide range of Random Graphs subjects, this volume examines series-parallel networks, properties of random subgraphs of the n-cube, …
This monograph provides and explains the mathematics behind geometric graph theory, which studies the properties of a graph that consists …
Most networks and databases that humans have to deal with contain large, albeit finite number of units. Their structure, for …
Eigenvalues and the Laplacian of a graph. The Laplacian and eigenvalues. Basic facts about the spectrum of a graph. Eigenvalues …
Spectral graph theory starts by associating matrices to graphs – notably, the adjacency matrix and the Laplacian matrix. The general …
From the Back Cover This textbook covers a diversity of topics in graph and network theory, both from a theoretical …
This book is a gentle introduction to the enumerative part of combinatorics suitable for study at the advanced undergraduate or …
This update of the 1987 title of the same name is an examination of what is currently known about the …
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