Deng L., Yu D. Deep Learning. Methods and Applications

NOWPress, 2013. — 198 p.This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise or knowledge of the authors; (2) the application areas that have already been transformed by the successful use of deep learning technology, such as speech recognition and computer vision; and (3) the application areas that have the potential to be impacted significantly by deep learning and that have been experiencing research growth, including natural language and text processing, information retrieval, and multimodal information processing empowered by multi-task deep learning.Some Historical Context of Deep Learning
Three Classes of Deep Learning Networks
Deep Autoencoders — Unsupervised Learning
Pre-Trained Deep Neural Networks — A Hybrid
Deep Stacking Networks and Variants — Supervised Learning
Selected Applications in Speech and Audio Processing
Selected Applications in Language Modeling and Natural Language Processing
Selected Applications in Information Retrieval
Selected Applications in Object Recognition and Computer Vision
Selected Applications in Multimodal and Multi-task Learning