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Data/moment-driven approaches for fast predictive control of collective dynamics
The high-dimensional character of collective dynamics hampers the performance of traditional MPC algorithms based on fast online dynamic optimization at every time step.
Reproducing kernel Hilbert spaces in the mean field limit
Kernel methods, being supported by a well-developed theory and coming with efficient algorithms, are among the most popular and successful machine learning techniques.
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