Accelerated Optimization for Machine Learning is popular PDF and ePub book, written by Zhouchen Lin in 2020-05-29, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Accelerated Optimization for Machine Learning can be Read Online from any device for your convenience.
Accelerated Optimization for Machine Learning Book PDF Summary
This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning. Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where the algorithms can be synchronous or asynchronous, for unconstrained and constrained problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well as for graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time.
Detail Book of Accelerated Optimization for Machine Learning PDF
- Author : Zhouchen Lin
- Release : 29 May 2020
- Publisher : Springer Nature
- ISBN : 9789811529108
- Genre : Computers
- Total Page : 286 pages
- Language : English
- PDF File Size : 19,5 Mb
If you're still pondering over how to secure a PDF or EPUB version of the book Accelerated Optimization for Machine Learning by Zhouchen Lin, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.