{"date_created":"2023-10-19T08:26:35Z","doi":"10.18653/v1/2022.acl-short.87","publication_status":"published","_id":"48298","status":"public","author":[{"first_name":"Ivan","id":"101881","full_name":"Habernal, Ivan","last_name":"Habernal"}],"year":"2022","user_id":"15504","publisher":"Association for Computational Linguistics","type":"conference","citation":{"apa":"Habernal, I. (2022). How reparametrization trick broke differentially-private text representation learning. <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</i>. <a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">https://doi.org/10.18653/v1/2022.acl-short.87</a>","chicago":"Habernal, Ivan. “How Reparametrization Trick Broke Differentially-Private Text Representation Learning.” In <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</i>. Association for Computational Linguistics, 2022. <a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">https://doi.org/10.18653/v1/2022.acl-short.87</a>.","mla":"Habernal, Ivan. “How Reparametrization Trick Broke Differentially-Private Text Representation Learning.” <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</i>, Association for Computational Linguistics, 2022, doi:<a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">10.18653/v1/2022.acl-short.87</a>.","ieee":"I. Habernal, “How reparametrization trick broke differentially-private text representation learning,” 2022, doi: <a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">10.18653/v1/2022.acl-short.87</a>.","bibtex":"@inproceedings{Habernal_2022, title={How reparametrization trick broke differentially-private text representation learning}, DOI={<a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">10.18653/v1/2022.acl-short.87</a>}, booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)}, publisher={Association for Computational Linguistics}, author={Habernal, Ivan}, year={2022} }","ama":"Habernal I. How reparametrization trick broke differentially-private text representation learning. In: <i>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</i>. Association for Computational Linguistics; 2022. doi:<a href=\"https://doi.org/10.18653/v1/2022.acl-short.87\">10.18653/v1/2022.acl-short.87</a>","short":"I. Habernal, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Association for Computational Linguistics, 2022."},"department":[{"_id":"34"},{"_id":"820"}],"language":[{"iso":"eng"}],"date_updated":"2023-10-19T12:05:39Z","title":"How reparametrization trick broke differentially-private text representation learning","publication":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)"}