| dc.contributor.author | Liu, Brian | |
| dc.contributor.author | Mazumder, Rahul | |
| dc.date.accessioned | 2023-09-08T13:24:06Z | |
| dc.date.available | 2023-09-08T13:24:06Z | |
| dc.date.issued | 2023-08-06 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/152040 | |
| dc.publisher | ACM|Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | en_US |
| dc.relation.isversionof | https://doi.org/10.1145/3580305.3599353 | 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 | Association for Computing Machinery | en_US |
| dc.title | FIRE: An Optimization Approach for Fast Interpretable Rule Extraction | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Liu, Brian and Mazumder, Rahul. 2023. "FIRE: An Optimization Approach for Fast Interpretable Rule Extraction." | |
| dc.contributor.department | Statistics and Data Science Center (Massachusetts Institute of Technology) | |
| dc.contributor.department | Sloan School of Management | |
| dc.contributor.department | Massachusetts Institute of Technology. Operations Research Center | |
| dc.identifier.mitlicense | PUBLISHER_CC | |
| 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 | 2023-09-01T07:46:26Z | |
| dc.language.rfc3066 | en | |
| dc.rights.holder | The author(s) | |
| dspace.date.submission | 2023-09-01T07:46:26Z | |
| mit.license | PUBLISHER_POLICY | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
