![]() | Machine Learning on Commodity Tiny Devices: Theory and Practice Subjects: Computer Science; Engineering & Technology; Algorithms & Complexity; Artificial Intelligence; Systems & Control Engineering; Machine Learning - Design; Neural Networks; Machine Learning; This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. It presents on-device learning techniques covering model-level neural network design, algorithm-level training optimization, and hardware-level instruction acceleration. Song Guo is a Full Professor leading the Edge Intelligence Lab and Research Group of Networking and Mobile Computing at the Hong Kong Polytechnic University. Professor Guo is a Fellow of the Canadian Academy of Engineering, Fellow of the IEEE, Fellow of the AAIA, and Clarivate Highly Cited Researcher. Qihua Zhou is a Ph.D. student with the Department of Computing, at the Hong Kong Polytechnic University. His research interests include distributed AI systems, large-scale parallel processing, tiny ML systems and domain-specific accelerators. |
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