Dongsheng Li – författare

This book constitutes the refereed proceedings of the 13th Conference on Advanced Computer Architecture, ACA 2020, held in Kunming, China, in August 2020. Due to the COVID-19 pandemic the conference was held online. 

The 24 revised full papers presented were carefully reviewed and selected from 105 submissions. The papers of this volume are organized in topical sections on: interconnection network, router and network interface architecture; accelerator-based, application-specific and reconfigurable architecture; processor, memory, and storage systems architecture; model, simulation and evaluation of architecture; new trends of technologies and applications.

This book starts from the classic recommendation algorithms, introduces readers to the basic principles and main concepts of the traditional algorithms, and analyzes their advantages and limitations. Then, it addresses the fundamentals of deep learning, focusing on the deep-learning-based technology used, and analyzes problems arising in the theory and practice of recommender systems, helping readers gain a deeper understanding of the cutting-edge technology used in these systems. Lastly, it shares practical experience with Microsoft ''s open source project Microsoft Recommenders. Readers can learn the design principles of recommendation algorithms using the source code provided in this book, allowing them to quickly build accurate and efficient recommender systems from scratch.