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Lukas Wutschitz
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2020 – today
- 2024
- [j3]Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz:
Numerical Composition of Differential Privacy. J. Priv. Confidentiality 14(1) (2024) - [j2]Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath
, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang:
Differentially Private Fine-tuning of Language Models. J. Priv. Confidentiality 14(2) (2024) - [c7]Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella Béguelin:
Closed-Form Bounds for DP-SGD against Record-level Inference. USENIX Security Symposium 2024 - [i9]Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella Béguelin:
Closed-Form Bounds for DP-SGD against Record-level Inference. CoRR abs/2402.14397 (2024) - [i8]Shoaib Ahmed Siddiqui, Radhika Gaonkar, Boris Köpf, David Krueger, Andrew Paverd, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Menglin Xia, Santiago Zanella Béguelin:
Permissive Information-Flow Analysis for Large Language Models. CoRR abs/2410.03055 (2024) - 2023
- [c6]Santiago Zanella Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Rühle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones:
Bayesian Estimation of Differential Privacy. ICML 2023: 40624-40636 - [c5]Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella Béguelin:
Analyzing Leakage of Personally Identifiable Information in Language Models. SP 2023: 346-363 - [i7]Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella Béguelin:
Analyzing Leakage of Personally Identifiable Information in Language Models. CoRR abs/2302.00539 (2023) - [i6]Lukas Wutschitz, Boris Köpf, Andrew Paverd, Saravan Rajmohan, Ahmed Salem, Shruti Tople, Santiago Zanella Béguelin, Menglin Xia, Victor Rühle:
Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective. CoRR abs/2311.15792 (2023) - 2022
- [c4]Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang:
Differentially Private Fine-tuning of Language Models. ICLR 2022 - [c3]Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni:
Differentially Private Model Compression. NeurIPS 2022 - [i5]Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni:
Differentially Private Model Compression. CoRR abs/2206.01838 (2022) - [i4]Santiago Zanella Béguelin
Bayesian Estimation of Differential Privacy. CoRR abs/2206.05199 (2022) - 2021
- [c2]Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz:
Numerical Composition of Differential Privacy. NeurIPS 2021: 11631-11642 - [i3]Huseyin A. Inan, Osman Ramadan, Lukas Wutschitz, Daniel Jones, Victor Rühle, James Withers, Robert Sim:
Privacy Analysis in Language Models via Training Data Leakage Report. CoRR abs/2101.05405 (2021) - [i2]Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz:
Numerical Composition of Differential Privacy. CoRR abs/2106.02848 (2021) - [i1]Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang:
Differentially Private Fine-tuning of Language Models. CoRR abs/2110.06500 (2021) - 2020
- [j1]Rei Yamashita
A full-field simulation methodology for sonic boom modeling on adaptive Cartesian cut-cell meshes. J. Comput. Phys. 408: 109271 (2020) - [c1]Santiago Zanella Béguelin, Lukas Wutschitz, Shruti Tople, Victor Rühle, Andrew Paverd, Olga Ohrimenko
Analyzing Information Leakage of Updates to Natural Language Models. CCS 2020: 363-375
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