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Learning Ising models from one or multiple samples
| dc.contributor.author | Dagan, Yuval | |
| dc.contributor.author | Daskalakis, Constantinos | |
| dc.contributor.author | Dikkala, Nishanth | |
| dc.contributor.author | Kandiros, Anthimos Vardis | |
| dc.date.accessioned | 2022-06-17T16:15:43Z | |
| dc.date.available | 2022-06-17T16:15:43Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/143465 | |
| dc.language.iso | en | |
| dc.publisher | Association for Computing Machinery (ACM) | en_US |
| dc.relation.isversionof | 10.1145/3406325.3451074 | en_US |
| dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
| dc.source | arXiv | 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. | |
| dc.relation.journal | Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing | en_US |
| dc.eprint.version | Original manuscript | 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 | OPEN_ACCESS_POLICY | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
