Learning Ising models from one or multiple samples
Name
3406325.3451074.pdf
Size
688.94 KB
Format
Adobe PDF
Checksum (MD5)
6c08a160bb9fa68640be1bef338f8534
Author(s)
Dagan, Yuval
Daskalakis, Constantinos
Dikkala, Nishanth
Kandiros, Anthimos Vardis
Date Issued
2021
Journal
Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing
Publisher
Association for Computing Machinery (ACM)
Citation
Dagan, Yuval, Daskalakis, Constantinos, Dikkala, Nishanth and Kandiros, Anthimos Vardis. 2021. "Learning Ising models from one or multiple samples." Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing.
Version
Final published version
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
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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DOI of Published Version
https://doi.org/10.1145/3406325.3451074
