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Patterns of Scalable Bayesian Inference - Foundations and Trends (R) in Machine Learning Elaine Angelino
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Patterns of Scalable Bayesian Inference - Foundations and Trends (R) in Machine Learning
Elaine Angelino
Identifies unifying principles, patterns, and intuitions for scaling Bayesian inference. This book examines how these techniques can be scaled up to larger problems and scaled out across parallel computational resources, and reviews existing work on utilizing computing resources with both MCMC and variational approximation techniques.
148 pages
| Media | Books Paperback Book (Book with soft cover and glued back) |
| Released | November 17, 2016 |
| ISBN13 | 9781680832181 |
| Publishers | now publishers Inc |
| Pages | 148 |
| Dimensions | 156 × 234 × 8 mm · 217 g |
| Language | English |
See all of Elaine Angelino ( e.g. Paperback Book )