Accelerated Optimization for Machine Learning (PDF)
- Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
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.
Huan Li received his Ph.D. degree in machine learning from Peking University in 2019. He is currently an Assistant Professor at the College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics. His current research interests include optimization and machine learning.
Cong Fang received his Ph.D. degree from Peking University in 2019. He is currently a Postdoctoral Researcher at Princeton University. His research interests include machine learning and optimization.
- Autoren: Zhouchen Lin , Huan Li , Cong Fang
- 2020, 1st ed. 2020, 275 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 9811529108
- ISBN-13: 9789811529108
- Erscheinungsdatum: 29.05.2020
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Grösse: 2.70 MB
- Ohne Kopierschutz
- Vorlesefunktion
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Accelerated Optimization for Machine Learning".
Kommentar verfassen