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Publication search results
found 93 matches
- 2023
- Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu:
Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. IEEE Data Eng. Bull. 46(1): 145-157 (2023) - Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock:
Reconciling Security and Communication Efficiency in Federated Learning. IEEE Data Eng. Bull. 46(1): 67-78 (2023) - Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael G. Rabbat, Carole-Jean Wu, Ilya Mironov:
Green Federated Learning. CoRR abs/2303.14604 (2023) - 2022
- Pierre Stock, Igor Shilov, Ilya Mironov, Alexandre Sablayrolles:
Defending against Reconstruction Attacks with Rényi Differential Privacy. CoRR abs/2202.07623 (2022) - Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu:
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning. CoRR abs/2206.03852 (2022) - Karthik Prasad, Sayan Ghosh, Graham Cormode, Ilya Mironov, Ashkan Yousefpour, Pierre Stock:
Reconciling Security and Communication Efficiency in Federated Learning. CoRR abs/2207.12779 (2022) - 2021
- Mani Malek Esmaeili, Ilya Mironov, Karthik Prasad, Igor Shilov, Florian Tramèr:
Antipodes of Label Differential Privacy: PATE and ALIBI. NeurIPS 2021: 6934-6945 - Huanyu Zhang, Ilya Mironov, Meisam Hejazinia:
Wide Network Learning with Differential Privacy. CoRR abs/2103.01294 (2021) - Mani Malek, Ilya Mironov, Karthik Prasad, Igor Shilov, Florian Tramèr:
Antipodes of Label Differential Privacy: PATE and ALIBI. CoRR abs/2106.03408 (2021) - Ashkan Yousefpour, Igor Shilov, Alexandre Sablayrolles, Davide Testuggine, Karthik Prasad, Mani Malek, John Nguyen, Sayan Ghosh, Akash Bharadwaj, Jessica Zhao, Graham Cormode, Ilya Mironov:
Opacus: User-Friendly Differential Privacy Library in PyTorch. CoRR abs/2109.12298 (2021) - Sen Yuan, Milan Shen, Ilya Mironov, Anderson C. A. Nascimento:
Practical, Label Private Deep Learning Training based on Secure Multiparty Computation and Differential Privacy. IACR Cryptol. ePrint Arch. 2021: 835 (2021) - 2020
- Nicholas Carlini, Matthew Jagielski, Ilya Mironov:
Cryptanalytic Extraction of Neural Network Models. CRYPTO (3) 2020: 189-218 - Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Shuang Song, Kunal Talwar, Abhradeep Thakurta:
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation. CoRR abs/2001.03618 (2020) - Nicholas Carlini, Matthew Jagielski, Ilya Mironov:
Cryptanalytic Extraction of Neural Network Models. CoRR abs/2003.04884 (2020) - 2019
- Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Abhradeep Thakurta:
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity. SODA 2019: 2468-2479 - Krishnaram Kenthapadi, Ilya Mironov, Abhradeep Guha Thakurta:
Privacy-preserving Data Mining in Industry. WSDM 2019: 840-841 - Krishnaram Kenthapadi, Ilya Mironov, Abhradeep Thakurta:
Privacy-preserving Data Mining in Industry. WWW (Companion Volume) 2019: 1308-1310 - Úlfar Erlingsson, Ilya Mironov, Ananth Raghunathan, Shuang Song:
That which we call private. CoRR abs/1908.03566 (2019) - Ilya Mironov, Kunal Talwar, Li Zhang:
Rényi Differential Privacy of the Sampled Gaussian Mechanism. CoRR abs/1908.10530 (2019) - 2018
- Ilya Mironov, Omkant Pandey, Omer Reingold, Gil Segev:
Incremental Deterministic Public-Key Encryption. J. Cryptol. 31(1): 134-161 (2018) - Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta:
Privacy Amplification by Iteration. FOCS 2018: 521-532 - Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Úlfar Erlingsson:
Scalable Private Learning with PATE. ICLR 2018 - Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Úlfar Erlingsson:
Scalable Private Learning with PATE. CoRR abs/1802.08908 (2018) - Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta:
Privacy Amplification by Iteration. CoRR abs/1808.06651 (2018) - Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Abhradeep Thakurta:
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity. CoRR abs/1811.12469 (2018) - 2017
- Martín Abadi, Úlfar Erlingsson, Ian J. Goodfellow, H. Brendan McMahan, Ilya Mironov, Nicolas Papernot, Kunal Talwar, Li Zhang:
On the Protection of Private Information in Machine Learning Systems: Two Recent Approches. CSF 2017: 1-6 - Ilya Mironov:
Rényi Differential Privacy. CSF 2017: 263-275 - Andrea Bittau, Úlfar Erlingsson, Petros Maniatis, Ilya Mironov, Ananth Raghunathan, David Lie, Mitch Rudominer, Ushasree Kode, Julien Tinnés, Bernhard Seefeld:
Prochlo: Strong Privacy for Analytics in the Crowd. SOSP 2017: 441-459 - Ilya Mironov, Gil Segev, Ido Shahaf:
Strengthening the Security of Encrypted Databases: Non-transitive JOINs. TCC (2) 2017: 631-661 - Ilya Mironov:
Renyi Differential Privacy. CoRR abs/1702.07476 (2017)
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