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... Læs mere
This book provides a practical introduction to compressive imaging (with examples and code), an overview of core topics, and a comprehensive, rigorous... Læs mere
This book introduces machine learning in finance and illustrates how to integrate computational tools with numerical finance with real world applications.
An intuitive, accessible text explaining the fundamentals and applications of signal processing on graphs. It covers basic and advanced topics, includes numerous... Læs mere
This book is a text intended for advanced undergraduates or graduate students which provides theoretical tools for analyzing and designing a large class... Læs mere
Machine learning algorithms hold out extraordinary promise, but the reality is that their success depends entirely on the suitability of the data... Læs mere
This is the first rigorous, self-contained treatment of the theory of deep learning. Aimed at scientists, instructors, and students interested in artificial intelligence and... Læs mere
Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is... Læs mere