2nd Edition
Mining Complex Networks
Part 1. Core Material
1. Graph Theory
2. Random Graph Models
3. Centrality Measures
4. Degree Correlations
5. Community Detection
6. Graph Embeddings
7. Hypergraphs
Part 2. Additional Material
8. Detecting Overlapping Communities
9. Embedding Graphs
10. Network Robustness
11. Road Networks
12. Fairness in Graph Mining
Biography
Bogumił Kamiński is the Chairman of the Scientific Council for the Discipline of Economics and Finance at SGH Warsaw School of Economics. He is an expert in applications of mathematical modelling and artificial intelligence models to solve complex real-life problems. He is also a substantial opensource contributor to the development of the Julia language and its package ecosystem.
Paweł Prałat is a Professor of Mathematics at Toronto Metropolitan University, whose main research interests are in random graph theory, especially in modelling and mining complex networks. He has pursued collaborations with various industry partners as well as the Government of Canada. He has written more than 230 papers and 4 books with more than 170 collaborators.
François Théberge holds a BSc degree in applied mathematics from the University of Ottawa, an MSc in telecommunications from INRS, and a PhD in electrical engineering from McGill University. He has been employed by the Government of Canada since 1996 during which he was involved in the creation of the data science team as well as the research group now known as the Tutte Institute for Mathematics and Computing. He also holds an adjunct professorial position in the Department of Mathematics and Statistics at the University of Ottawa.
