Feng Dai

Yuan Xu

This monograph records progress in approximation theory and harmonic analysis on balls and spheres, and presents contemporary material that will be useful to analysts in this area. While the first part of the book contains mainstream material on the subject, the second and the third parts deal with more specialized topics, such as analysis in weight spaces with reflection invariant weight functions, and analysis on balls and simplexes. The last part of the book features several applications, including cubature formulas, distribution of points on the sphere, and the reconstruction algorithm in computerized tomography. This book is directed at researchers and advanced graduate students in analysis. Mathematicians who are familiar with Fourier analysis and harmonic analysis will understand many of the concepts that appear in this manuscript: spherical harmonics, the Hardy-Littlewood maximal function, the Marcinkiewicz multiplier theorem, the Riesz transform, and doubling weights are all familiar tools to researchers in this area.

Approximation Theory and Harmonic Analysis on Spheres and Balls

Charles F. Dunkl

Orthogonal polynomials of several variables, approximation theory, symmetry-group methods.

Orthogonal Polynomials of Several Variables

Jin Li

Hongyang Yan

Jun Cai

Huang Teng

The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.

4th International Conference, ML4CS 2022, Guangzhou, China, December 2–4, 2022, Proceedings, Part I

Machine Learning for Cyber Security

Updated throughout, this revised edition contains 25% new material covering progress made in the field over the past decade.

Yuan Xu

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