Special Session on Mathematics of Data Science and Applications
|
Organizer(s): |
Name:
|
Affiliation:
|
Country:
|
Ding-Xuan Zhou
|
dingxuan.zhou@sydney.edu.au
|
Australia
|
Xiang Zhou
|
City University of Hong Kong
|
Hong Kong
|
|
|
|
|
|
|
|
|
Introduction:
| | Over the last twenty years, data science, machine learning, and deep learning in particular, have begun transforming the global economy and modern life. While much attention is focused on empirical data mining success, there have been considerable mathematical structures and a growing body of mathematical theories about how the structures relate to observable properties of real-world systems. Discovering such structures may lead to important mathematical insights and implications for practitioners. This special session aims at interactions among approximation theory, deep neural networks, harmonic analysis, machine learning, numerical analysis, and statistics to foster further research in the fast-developing area of data science.
|
|
|
|
| |
