Hamiltonian Monte Carlo Methods in Machine Learning (eBook)

Tshilidzi Marwala, Rendani Mbuvha, Wilson Tsakane Mongwe (Autoren)

eBook Download: PDF | EPUB

2023 | 1. Auflage
220 Seiten
Elsevier Science (Verlag)
978-0-443-19036-0 (ISBN)

Infos

Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup. Lastly, the authors address the critical issues of variance reduction for parameter estimates of numerous HMC based samplers. The book offers a comprehensive introduction to Hamiltonian Monte Carlo methods and provides a cutting-edge exposition of the current pathologies of HMC-based methods in both tuning, scaling and sampling complex real-world posteriors. These are mainly in the scaling of inference (e.g., Deep Neural Networks), tuning of performance-sensitive sampling parameters and high sample autocorrelation. Other sections provide numerous solutions to potential pitfalls, presenting advanced HMC methods with applications in renewable energy, finance and image classification for biomedical applications. Readers will get acquainted with both HMC sampling theory and algorithm implementation. - Provides in-depth analysis for conducting optimal tuning of Hamiltonian Monte Carlo (HMC) parameters - Presents readers with an introduction and improvements on Shadow HMC methods as well as non-canonical HMC methods - Demonstrates how to perform variance reduction for numerous HMC-based samplers - Includes source code from applications and algorithms

Dr. Tshilidzi Marwala is the Rector of the United Nations (UN) University and the UN Under-Secretary-General from 1 March 2023. He was previously the Vice-Chancellor and Principal of the University of Johannesburg, Deputy Vice-Chancellor for Research and Executive Dean of the Faculty of Engineering at the University of Johannesburg. He was Associate Professor, Full Professor, the Carl and Emily Fuchs Chair of Systems and Control Engineering at the University of the Witwatersrand. He holds a Bachelor of Science in Mechanical Engineering (magna cum laude) from Case Western Reserve University, a Master of Mechanical Engineering from the University of Pretoria, PhD in Artificial Intelligence from the University of Cambridge and a Post-Doc at Imperial College (London). He is a registered professional engineer, a Fellow of TWAS (The World Academy of Sciences), the Academy of Science of South Africa, the African Academy of Sciences and the South African Academy of Engineering. He is a Senior Member of the IEEE and a distinguished member of the ACM. His research interests are multi-disciplinary and they include the theory and application of artificial intelligence toengineering, computer science, finance, social science and medicine. He has supervised 28 Doctoral students published 15 books in artificial intelligence (one translated into Chinese), over 300 papers in journals, proceedings, book chapters and magazines and holds five patents. He is an associate editor of the International Journal of Systems Science (Taylor and Francis Publishers). He has been a visiting scholar at Harvard University, University of California at Berkeley, Wolfson College of the University of Cambridge, Nanjing Tech University and Silesian University of Technology in Poland. His opinions have appeared in the New Scientist, The Economist, Time Magazine, BBC, CNN and the Oxford Union. Dr. Marwala is the author of Rational Machines and Artificial Intelligence from Elsevier Academic Press.

Produkt-Details

• Erscheint lt. Verlag: 3.2.2023
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• ISBN-10: 0-443-19036-4 / 0443190364
• ISBN-13: 978-0-443-19036-0 / 9780443190360