| dc.contributor.author | Daskalakis, Constantinos | |
| dc.contributor.author | Pan, Qinxuan | |
| dc.date.accessioned | 2022-06-17T16:21:12Z | |
| dc.date.available | 2022-06-17T16:21:12Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/143466 | |
| dc.language.iso | en | |
| dc.publisher | Association for Computing Machinery (ACM) | en_US |
| dc.relation.isversionof | 10.1145/3406325.3451006 | en_US |
| dc.rights | Creative Commons Attribution 4.0 International license | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | ACM | en_US |
| dc.title | Sample-optimal and efficient learning of tree Ising models | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Daskalakis, Constantinos and Pan, Qinxuan. 2021. "Sample-optimal and efficient learning of tree Ising models." Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing. | |
| 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/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2022-06-17T16:15:23Z | |
| dspace.orderedauthors | Daskalakis, C; Pan, Q | en_US |
| dspace.date.submission | 2022-06-17T16:15:26Z | |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
