dc.contributor.author | Dagan, Yuval | |
dc.contributor.author | Daskalakis, Constantinos | |
dc.contributor.author | Dikkala, Nishanth | |
dc.contributor.author | Kandiros, Anthimos Vardis | |
dc.date.accessioned | 2022-10-27T18:48:50Z | |
dc.date.available | 2022-06-17T16:15:43Z | |
dc.date.available | 2022-10-27T18:48:50Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/143465.2 | |
dc.language.iso | en | |
dc.publisher | Association for Computing Machinery (ACM) | en_US |
dc.relation.isversionof | 10.1145/3406325.3451074 | en_US |
dc.rights | 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. | en_US |
dc.source | ACM | en_US |
dc.title | Learning Ising models from one or multiple samples | en_US |
dc.type | Article | en_US |
dc.identifier.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. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | |
dc.relation.journal | Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dc.date.updated | 2022-06-17T16:11:09Z | |
dspace.orderedauthors | Dagan, Y; Daskalakis, C; Dikkala, N; Kandiros, AV | en_US |
dspace.date.submission | 2022-06-17T16:11:11Z | |
mit.license | PUBLISHER_POLICY | |
mit.metadata.status | Authority Work and Publication Information Needed | en_US |