This book serves as a primer on a secure computing framework known as federated learning. Federated learning is the study of methods to enable multiple parties to collaboratively train machine learning/AI models, while each party retains its own, raw data on-premise, never sharing it with others. This book is designed to be accessible to anyone with a background in undergraduate applied mathematics. It covers the basics of topics from computer science that are needed to understand examples of simple federated computing frameworks. It is my hope that by learning basic concepts and technical...

This open access book contains review/research papers authored by fourteen plenary/invited speakers to the 10th International Congress on Industrial and Applied Mathematics (Tokyo, August 20 25, 2023). Written by top-level scientists recognized worldwide, this book covers a wide range topics at the frontline of industrial and applied mathematics. Some of them contain a kind of tutorial, some contain quite readable surveys. We are sure that offering these papers will be a great service to the community of industrial and applied mathematics. This book, which is the Volume 1 of a thematic...