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https://www.math.cuhk.edu.hk/course/mmat5391
... foundations of and optimization techniques used in machine learning. Both theoretical and numerical approaches for tackling mathematical problems arising from machine learning will be introduced. Learning will be enhanced through software ...
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https://www.math.cuhk.edu.hk/course/math3340
... the fundamental mathematical theory for modern machine learning techniques, including empirical risk minimization (error ...
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https://www.math.cuhk.edu.hk/e-learning/online-e-learning-center
The online E-Learning Center provides links to e-learning materials developed by our teachers. These include several e-learning modules and two role-playing games.
List of E-Learning Materials ...
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https://www.math.cuhk.edu.hk/seminars/machine-learning-and-computational-mathematics-0
... University Abstract: The heart of machine learning is the approximation of functions using finite pieces of data. This ... Thus it is not surprising that the success of machine learning in dealing with functions in very high dimensions has opened up some ...
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https://www.math.cuhk.edu.hk/seminars/discretization-invariant-operator-learning-algorithms-and-theory
... University of Maryland Abstract: Learning operators between infinitely dimensional spaces is an important learning task arising in wide applications in machine learning, data science, ...
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https://www.math.cuhk.edu.hk/seminars/two-approaches-using-deep-learning-solve-partial-differential-equations
... Recently, new numerical approaches using machine learning and deep learning have been actively studied. There are two mainstream deep learning ...
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https://www.math.cuhk.edu.hk/seminars/inverse-problems-seminar-operator-learning-nonsmooth-optimal-control-pdes
... these challenges numerically, we propose an operator learning approach combined with an effective primal-dual optimization idea that ... neural surrogate models for the involved PDEs by operator learning, allowing the solution of a PDE to be obtained with only a forward ...
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https://www.math.cuhk.edu.hk/seminars/mathematical-theory-deep-learning
... University of Hong Kong Abstract: Deep learning has been widely applied and brought breakthroughs in speech ... and computational issues have been well studied in machine learning. But there lacks a theoretical foundation for understanding the ...
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https://www.math.cuhk.edu.hk/seminars/learning-operators-identifying-weak-solutions-navier-stokes-equations
... Abstract: We employ a combination of deep learning methods and compactness argument to derive learning operators for weak solutions of Navier-Stokes equations for any large ...
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https://www.math.cuhk.edu.hk/course/2122/mmat5391
Course Name: Mathematical Theories of Machine Learning Teacher: Dr. Hiu Ning CHAN Course ...
