High-Dimensional Data Analysis with Low-Dimensional Models:
Principles, Computation, and Applications

John Wright and Yi Ma,   Cambridge University Press

Basic Information

The book covers new mathematical principles (statistics and geometry) for high-dimensional data analysis, scalable (convex and nonconvex) optimization methods, and important applications such as scientific imaging, wideband communications, face recognition, 3D vision, and deep networks. This book is to be used as an introductory graduate textbook for the areas of data science, signal processing, optimization, and machine learning. It has been used for the courses EECS 290 (Berkeley) and ELEN 6886 (Columbia).

Download and Copyright

Download a pre-production copy: Book-Wright-Ma.pdf (full book coming soon). Copyright of this book is held by Cambridge University Press, who have kindly allowed us to post a pre-publication version on this website.

Copyright statement: This material will be published by Cambridge University Press as "High-Dimensional Data Analysis with Low-Dimensional Models: Principles, Computation, and Applications" by John Wright and Yi Ma. This pre-publication version is free to view and download for personal use only, and is not for redistribution, re-sale or use in derivative works. Copyright © Cambridge University Press 2018.

Catalog Links

Hardcopy of the book is available at: TBA

Errata and Resources

Reader feedback: If you have any feedback, suggestions, or errors to report, please send us an email to: book.wright.ma@gmail.com

Errata: TBA

Additional resources: TBA

©2020 Yi Ma
Last modified: Sat Nov 21 15:40:08 PST 2020