Most recent volume

Volume . Deep Learning Through Sparse and Low-Rank Modeling

Published: 1st May 2019 Authors: Zhangyang Wang Yun Raymond Thomas Huang

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.

Additional volumes

Multimodal Behavior Analysis in the Wild

Published: 1st November 2018 Editors: Xavier Alameda-Pineda Elisa Ricci Nicu Sebe

Spectral Geometry of Shapes

Published: 1st October 2018 Authors: Jing Hua Zichun Zhong

Computer Vision for Assistive Healthcare

Published: 16th May 2018 Editors: Leo Marco Giovanni Maria Farinella

Low-Rank Models in Visual Analysis

Published: 5th June 2017 Authors: Zhouchen Lin Hongyang Zhang