Contributor
Heng, Liao, editor.
ImprintCambridge, United Kingdom ; New York, NY : Cambridge University Press, 2022.
Descriptionx, 387 pages : illustrations (some color) ; 25 cm
Note:Part I. Computing -- Mathematics, models and architectures / Bill McColl -- Mathematics and software verification / Chen Haibo and Gao Xin -- Mathematics for quantum computing / Kong Yunchuan -- Mathematics for AI: categories, toposes, types / Daniel Bennequin and Jean-Claude Belfiore -- Part II. Communications -- Mathematics and compressed sensing / Zhang Rui and Long Zichao -- Mathematics, information theory, and statistical physics / Merouane Debbah -- Mathematics of data networking / Li Zongpeng, Miao Lihua and Tang Siyu -- Mathematics and network science / Sun Jie -- Part III. Artificial Intelligence -- Mathematics, information and learning / Tong Wen and Ge Yiqun -- Mathematics and Bayesian inference / Guo Kaiyang, Lv Wenlong and Zhang Jianfeng -- Mathematics, optimization and machine learning / Jiu Shangling -- Mathematics of reinforcement learning / Wu Shuang and Wang Jun -- Part IV. Future -- Mathematics and prospects for future breakthroughs / Dang Wenshuan.
Bibliography Note:Includes bibliographical references.
Note:For 80 years, mathematics has driven fundamental innovation in computing and communications. This timely book provides a panorama of some recent ideas in mathematics and how they will drive continued innovation in computing, communications and AI in the coming years. It provides a unique insight into how the new techniques that are being developed can be used to provide theoretical foundations for technological progress, just as mathematics was used in earlier times by Turing, von Neumann, Shannon and others. Edited by leading researchers in the field, chapters cover the application of new mathematics in computer architecture, software verification, quantum computing, compressed sensing, networking, Bayesian inference, machine learning, reinforcement learning and many other areas.
