Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean 
Embedding in Moment Problem

Zhu, Jia-Jie; Jitkrittum, Wittawat; Diehl, Moritz; Schölkopf, Bernhard

doi:10.1109/CDC42340.2020.9303938

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Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem

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Zhu, Jia-Jie
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Jitkrittum, Wittawat
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Schölkopf, Bernhard
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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https://doi.org/10.48550/arXiv.2004.00166
(Preprint)

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Zhu, J.-J., Jitkrittum, W., Diehl, M., & Schölkopf, B. (2021). Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem. In 2020 59th IEEE Conference on Decision and Control (CDC 2020) (pp. 3457-3463). Piscataway, NJ: IEEE. doi:10.1109/CDC42340.2020.9303938.

Cite as: https://hdl.handle.net/21.11116/0000-000A-F4B4-7

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