Deep Learning through Sparse and Low-Rank Modeling - Zhangyang Wang,Yun Fu,Thomas S. Huang
-30% with code BOOKS
Shipping in 10-16 days
30-day return policy
Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models-those that emphasize problem-specific Interpretability-with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety ... Full description
You May Also Like
TOP
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All
Eliezer Yudkowsky, Nate Soares
-30% with code BOOKS
In stock at our supplier
TOP
How To Think About AI: A Guide For The Perplexed
-30% with code BOOKS
In stock at our supplier
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-30% with code BOOKS
In stock at our supplier
TOP
AI Engineering: Building Applications with Foundation Models
-30% with code BOOKS
In stock at our supplier
TOP
Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI
-30% with code BOOKS
In stock at our supplier
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-30% with code BOOKS
In stock at our supplier
TOP
The Rust Programming Language
Steve Klabnik, Carol Nichols, Chris Krycho
-30% with code BOOKS
In stock at our supplier
TOP
How to Talk to AI: (And How Not To)
-30% with code BOOKS
In stock at our supplier
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-30% with code BOOKS
In stock at our supplier
TOP
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-30% with code BOOKS
In stock at our supplier
TOP
The Art of Game Design: A Book of Lenses
-30% with code BOOKS
In stock at our supplier
TOP
How Linux Works: What Every Superuser Should Know
-30% with code BOOKS
In stock at our supplier
TOP
Hands-On Large Language Models: Language Understanding and Generation
Maarten Grootendorst, Jay Alammar
-30% with code BOOKS
In stock at our supplier
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-30% with code BOOKS
In stock at our supplier
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-30% with code BOOKS
In stock at our supplier
TOP
Clean Architecture: A Craftsman's Guide to Software Structure and Design
-30% with code BOOKS
In stock at our supplier
TOP
World of Warcraft Chronicle, Volume 2
-30% with code BOOKS
In stock at our supplier
TOP
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
-30% with code BOOKS
In stock at our supplier
TOP
Deep Learning: Foundations and Concepts
Christopher M. Bishop, Hugh Bishop
-30% with code BOOKS
In stock at our supplier
Description
Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models-those that emphasize problem-specific Interpretability-with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide variety of applications in computer vision, machine learning, signal processing, and data mining.
This book will be highly useful for researchers, graduate students and practitioners working in the fields of computer vision, machine learning, signal processing, optimization and statistics.
More Information
| Author | Zhangyang Wang, Yun Fu, Thomas S. Huang |
|---|---|
| Publisher | Elsevier |
| Release year | 2019 |
| Cover type | Softcover |
| EAN | 9780128136591 |