How reparametrization trick broke differentially-private text representation learning
I. Habernal, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Association for Computational Linguistics, 2022.
Download
No fulltext has been uploaded.
Conference Paper
| Published
| English
Author
Publishing Year
Proceedings Title
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
LibreCat-ID
Cite this
Habernal I. How reparametrization trick broke differentially-private text representation learning. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Association for Computational Linguistics; 2022. doi:10.18653/v1/2022.acl-short.87
Habernal, I. (2022). How reparametrization trick broke differentially-private text representation learning. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). https://doi.org/10.18653/v1/2022.acl-short.87
@inproceedings{Habernal_2022, title={How reparametrization trick broke differentially-private text representation learning}, DOI={10.18653/v1/2022.acl-short.87}, 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} }
Habernal, Ivan. “How Reparametrization Trick Broke Differentially-Private Text Representation Learning.” In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Association for Computational Linguistics, 2022. https://doi.org/10.18653/v1/2022.acl-short.87.
I. Habernal, “How reparametrization trick broke differentially-private text representation learning,” 2022, doi: 10.18653/v1/2022.acl-short.87.
Habernal, Ivan. “How Reparametrization Trick Broke Differentially-Private Text Representation Learning.” Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Association for Computational Linguistics, 2022, doi:10.18653/v1/2022.acl-short.87.
Google Scholar