Mathematics of Data Science and Applications
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Organizer(s): |
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Affiliation:
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Country:
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Ding-xuan ZHOU
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The University of Sydney
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Australia
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Xiang ZHOU
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City University of Hong Kong
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Hong Kong
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Introduction:
| | Over the past a few decades, data science, machine learning, and deep learning, as the foundation of AI, have transformed the global economy and modern life. While much attention is focused on empirical success, there have been considerable mathematical structures and a growing body of mathematical theories about how the these advances 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, harmonic analysis, machine learning, numerical analysis, dynamical system and statistics to foster further research in the fast-developing area of data science.
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