Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational induct

This book is concerned with a fundamentally novel approach to graph-based pattern recognition based on vector space embedding of graphs. It aims at condensing t

This book constitutes the refereed proceedings of the bienially held International Conference on Computer Analysis of Images and Patterns, CAIP 2009, which took

This book constitutes the refereed proceedings of the 8th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2011, h