Download or Read online Deep Learning through Sparse and Low Rank Modeling full in PDF, ePub and kindle. this book written by Zhangyang Wang and published by Academic Press which was released on 15 May 2019 with total page 300 pages. We cannot guarantee that Deep Learning through Sparse and Low Rank Modeling book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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. Combines classical sparse and low-rank models and algorithms with the latest advances in deep learning networks Shows how the structure and algorithms of sparse and low-rank methods improves the performance and interpretability of Deep Learning models Provides tactics on how to build and apply customized deep learning models for various applications
Deep Learning through Sparse and Low Rank Modeling
- Author : Zhangyang Wang
- Publisher : Academic Press
- Pages : 300 pages
- ISBN : 0128136596
- Release : 15 May 2019
- Rating : /5 from reviews