{"user_id":"15504","author":[{"last_name":"Senge","full_name":"Senge, Manuel","first_name":"Manuel"},{"first_name":"Timour","last_name":"Igamberdiev","full_name":"Igamberdiev, Timour"},{"full_name":"Habernal, Ivan","last_name":"Habernal","first_name":"Ivan","id":"101881"}],"department":[{"_id":"34"},{"_id":"820"}],"title":"One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks","type":"conference","publication":"Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing","date_created":"2023-10-19T08:26:21Z","doi":"10.18653/v1/2022.emnlp-main.496","_id":"48297","status":"public","language":[{"iso":"eng"}],"year":"2023","citation":{"mla":"Senge, Manuel, et al. “One Size Does Not Fit All: Investigating Strategies for Differentially-Private Learning across NLP Tasks.” Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2023, doi:10.18653/v1/2022.emnlp-main.496.","short":"M. Senge, T. Igamberdiev, I. Habernal, in: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2023.","chicago":"Senge, Manuel, Timour Igamberdiev, and Ivan Habernal. “One Size Does Not Fit All: Investigating Strategies for Differentially-Private Learning across NLP Tasks.” In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2023. https://doi.org/10.18653/v1/2022.emnlp-main.496.","ieee":"M. Senge, T. Igamberdiev, and I. Habernal, “One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks,” 2023, doi: 10.18653/v1/2022.emnlp-main.496.","bibtex":"@inproceedings{Senge_Igamberdiev_Habernal_2023, title={One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks}, DOI={10.18653/v1/2022.emnlp-main.496}, booktitle={Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing}, publisher={Association for Computational Linguistics}, author={Senge, Manuel and Igamberdiev, Timour and Habernal, Ivan}, year={2023} }","apa":"Senge, M., Igamberdiev, T., & Habernal, I. (2023). One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. https://doi.org/10.18653/v1/2022.emnlp-main.496","ama":"Senge M, Igamberdiev T, Habernal I. One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics; 2023. doi:10.18653/v1/2022.emnlp-main.496"},"date_updated":"2023-10-19T12:05:55Z","publisher":"Association for Computational Linguistics","publication_status":"published"}