Binding: Paperback
Description: Deep neural networks (DN Ns) with their dense and complex algorithms provide real possibilities for Artificial General Intelligence (AGI). Meta - learning with DN Ns brings AGI much closer: artificial agents solving intelligent tasks that human beings can achieve even transcending what they can achieve. Meta - Learning: Theory Algorithms and Applications shows how meta - learning in combination with DN Ns advances towards AGI. Meta - Learning: Theory Algorithms and Applications explains the fundamentals of meta - learning by providing answers to these questions: What is meta - learning?; why do we need meta - learning?; how are self - improved meta - learning mechanisms heading for AGI ?; how can we use meta - learning in our approach to specific scenarios? The book presents the background of seven mainstream paradigms: meta - learning few - shot learning deep learning transfer learning machine learning probabilistic modeling and Bayesian inference. It then explains important state - of - the - art mechanisms and their variants for meta - learning including memory - augmented neural networks meta - networks convolutional Siamese neural networks matching networks prototypical networks relation networks LSTM meta - learning model - agnostic meta - learning and the Reptile algorithm. The book takes a deep dive into nearly 200 state - of - the - art meta - learning algorithms from top tier conferences (e. g. Neur IPS ICML CVPR ACL ICLR KDD). It systematically investigates 39 categories of tasks from 11 real - world application fields: Computer Vision Natural Language Processing Meta - Reinforcement Learning Healthcare Finance and Economy Construction Materials Graphic Neural Networks Program Synthesis Smart City Recommended Systems and Climate Science. Each application field concludes by looking at future trends or by giving a summary of available resources. Meta - Learning: Theory Algorithms and Applications is a great resource to understand the principles of meta - learning and to learn state - of - the - art meta - learning algorithms giving the student researcher and industry professional the ability to apply meta - learning for various novel applications.
Title: Meta - Learning Theory Algorithms And Applications
Author(s): Zou Lan (Columnist Association For The Advancement Of Artificial Intelligence (Https:// Aihub/) Researcher Ai Silicon Valley And Carnegie Mellon University)
Publisher: Elsevier Science & Technology
Barcode: 9780323899314
Pages: 402 Pages
Publication Date: 11/8/2022
Category: Neural Networks & Fuzzy Systems