Zhangyang (Atlas) Wang​

 Zhangyang Wang*, Yun Fu, and Thomas. S. Huang,

"Deep Learning through Sparse and Low-Rank Modeling"

Elsevier (CVPR series), 2019. ISBN: 978-012-813-659-1. [Link]


The book 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.