Marwala, Tshilidzi Author
Biography not available.
Browse all ART CRITICISM books
Browse all Ashworth books
Browse all FOLKLORE books
Browse all GARDENS books
Browse all GRAPHIC NOVELS books
Browse all Hamilton books
Browse all HISTORY - MEDIEVAL books
Browse all HUMOUR books
Browse all KINDRED books
Browse all LITERARY STUDIES books
Browse all LONDON books
Browse all Lozada books
Browse all Medical : Nursing - Mental Health books
Browse all MIND books
Browse all MUSEOLOGY books
Browse all NON-CLASSIFIABLE books
Browse all NONLINEAR SCIENCE books
Browse all Ormonde books
Browse all POPULAR SCIENCE books
Browse all RELIGIOUS STUDIES books
Browse all SPIRIT books
Browse all SPORT books
Browse all TRAVEL WRITING books
Out of Stock
Paperback ยท ISBN 9780443190353
Inclusive of GST and other taxes
Arriving at your doorstep in 10-15 days
Our logisitcs team will make sure everyitem is delivered safely
| ISBN | 9780443190353 |
|---|---|
| Publisher | Academic Press |
| Publication date | February 2023 |
| Language | English |
| MRP | ยฃ138.00 GBP |
| Page count | 222 |
| Item weight | 86 g |
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.
Log in to write a review for this book.
No reviews yet. Be the first to share your opinion.
Biography not available.
Biography not available.
Biography not available.