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Privacy accounting εconomics: Improving differential privacy composition via a posteriori bounds.

, , , and . Proc. Priv. Enhancing Technol., 2022 (3): 222-246 (2022)

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Distribution inference risks: Identifying and mitigating sources of leakage., , , , , and . CoRR, (2022)Language Model Decoding as Likelihood-Utility Alignment., , , , , , , , , and . EACL (Findings), page 1425-1440. Association for Computational Linguistics, (2023)Privacy accounting εconomics: Improving differential privacy composition via a posteriori bounds., , , and . Proc. Priv. Enhancing Technol., 2022 (3): 222-246 (2022)Distribution Inference Risks: Identifying and Mitigating Sources of Leakage., , , , , and . SaTML, page 136-149. IEEE, (2023)SoK: Memorization in General-Purpose Large Language Models., , , , , and . CoRR, (2023)Orderings of Data - More Than a Tripping Hazard: Visionary., , and . SSDBM, page 17:1-17:4. ACM, (2020)DiPPS: Differentially Private Propensity Scores for Bias Correction., , and . ICWSM, page 114-125. AAAI Press, (2023)On the Choice of Databases in Differential Privacy Composition., , and . CoRR, (2022)KISS - A fast kNN-based Importance Score for Subspaces., , , and . EDBT, page 391-396. OpenProceedings.org, (2021)Privacy-Preserving Classification with Secret Vector Machines., , , and . CIKM, page 475-484. ACM, (2020)