Deep Learning through Sparse and Low-Rank Modeling Wang Fu Huang Paperback

Deep Learning through Sparse and Low-Rank ModelingAuthor(s): Zhangyang Wang, Yun Fu, Thomas S. Huang\nFormat: Paperback\nPublisher: Elsevier Science Publishing Co Inc, United States\nImprint: Academic Press Inc\nISBN-13: 9780128136591, 978-0128136591\nSynopsis\nDeep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank modelsthose that emphasize problem-specific Interpretabilitywith 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.\n\nThis book will be highly useful for researchers, graduate studen.