Meta-Learning: Theory, Algorithms And Applications

Meta-Learning: An Overview explains the fundamentals of meta-learning, providing an understanding of the concept of learning to learn. After giving a background to artificial intelligence, machine learning, deep learning, deep reinforcement learning, and meta-learning, the book provides important state-of-the-art mechanisms 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 Reptile. The book then demonstrates the application of the principles and algorithms of meta learning in computer vision, meta-reinforcement learning, robotics, speech recognition, natural language processing, finance, business management and health care. A final chapter summarizes future trends. Users, including students and researchers will find updates on the principles and state-of-the-art meta-learning algorithms, thus enabling the use of meta-learning for a range of applications.

• | Author: Lan Zou
• | Publisher: Academic Press
• | Publication Date: Nov 08, 2022
• | Number of Pages: 402 pages
• | Language: English
• | Binding: Paperback/Computers
• | ISBN-10: 0323899315
• | ISBN-13: 9780323899314