| dc.contributor.author | Shanmugam, Divya | |
| dc.contributor.author | Diaz, Fernando | |
| dc.contributor.author | Shabanian, Samira | |
| dc.contributor.author | Finck, Michele | |
| dc.contributor.author | Biega, Asia | |
| dc.date.accessioned | 2022-11-10T18:48:19Z | |
| dc.date.available | 2022-11-10T18:48:19Z | |
| dc.date.issued | 2022-06-21 | |
| dc.identifier.isbn | 978-1-4503-9352-2 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/146342 | |
| dc.publisher | ACM|2022 ACM Conference on Fairness, Accountability, and Transparency | en_US |
| dc.relation.isversionof | https://doi.org/10.1145/3531146.3533148 | 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|2022 ACM Conference on Fairness, Accountability, and Transparency | en_US |
| dc.title | Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data Minimization | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Shanmugam, Divya, Diaz, Fernando, Shabanian, Samira, Finck, Michele and Biega, Asia. 2022. "Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data Minimization." | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| 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 | 2022-11-03T01:12:29Z | |
| dc.language.rfc3066 | en | |
| dc.rights.holder | The author(s) | |
| dspace.date.submission | 2022-11-03T01:12:29Z | |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
