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Settling the Robust Learnability of Mixtures of Gaussians

Author(s)
Liu, Allen; Moitra, Ankur
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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Date issued
2021-06-15
URI
https://hdl.handle.net/1721.1/145926
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Publisher
ACM|Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing
Citation
Liu, Allen and Moitra, Ankur. 2021. "Settling the Robust Learnability of Mixtures of Gaussians."
Version: Final published version
ISBN
978-1-4503-8053-9

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