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Mohammad Yaghini
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2020 – today
- 2023
- [c9]Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot:
Proof-of-Learning is Currently More Broken Than You Think. EuroS&P 2023: 797-816 - [c8]Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz:
Tubes Among Us: Analog Attack on Automatic Speaker Identification. USENIX Security Symposium 2023 - [i10]Mohammad Yaghini, Patty Liu, Franziska Boenisch, Nicolas Papernot:
Learning with Impartiality to Walk on the Pareto Frontier of Fairness, Privacy, and Utility. CoRR abs/2302.09183 (2023) - 2022
- [j1]Bogdan Kulynych
, Mohammad Yaghini, Giovanni Cherubin, Michael Veale
, Carmela Troncoso:
Disparate Vulnerability to Membership Inference Attacks. Proc. Priv. Enhancing Technol. 2022(1): 460-480 (2022) - [c7]Ali Shahin Shamsabadi, Mohammad Yaghini, Natalie Dullerud, Sierra Calanda Wyllie, Ulrich Aïvodji, Aisha Alaagib, Sébastien Gambs, Nicolas Papernot:
Washing The Unwashable : On The (Im)possibility of Fairwashing Detection. NeurIPS 2022 - [i9]Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz:
Pipe Overflow: Smashing Voice Authentication for Fun and Profit. CoRR abs/2202.02751 (2022) - [i8]Adam Dziedzic, Stephan Rabanser, Mohammad Yaghini, Armin Ale, Murat A. Erdogdu, Nicolas Papernot:
p-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations. CoRR abs/2207.12545 (2022) - [i7]Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot:
On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning. CoRR abs/2208.03567 (2022) - 2021
- [c6]Mohammad Yaghini, Andreas Krause, Hoda Heidari:
A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness. AIES 2021: 1023-1033 - [c5]Pratyush Maini, Mohammad Yaghini, Nicolas Papernot:
Dataset Inference: Ownership Resolution in Machine Learning. ICLR 2021 - [c4]Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot:
Proof-of-Learning: Definitions and Practice. SP 2021: 1039-1056 - [i6]Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot:
Proof-of-Learning: Definitions and Practice. CoRR abs/2103.05633 (2021) - [i5]Pratyush Maini, Mohammad Yaghini, Nicolas Papernot:
Dataset Inference: Ownership Resolution in Machine Learning. CoRR abs/2104.10706 (2021) - [i4]Varun Chandrasekaran, Hengrui Jia, Anvith Thudi, Adelin Travers, Mohammad Yaghini, Nicolas Papernot:
SoK: Machine Learning Governance. CoRR abs/2109.10870 (2021)
2010 – 2019
- 2019
- [i3]Mohammad Yaghini, Bogdan Kulynych, Carmela Troncoso:
Disparate Vulnerability: on the Unfairness of Privacy Attacks Against Machine Learning. CoRR abs/1906.00389 (2019) - [i2]Mohammad Yaghini, Hoda Heidari, Andreas Krause:
A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness. CoRR abs/1911.03020 (2019) - 2018
- [c3]Naman Goel, Mohammad Yaghini, Boi Faltings:
Non-Discriminatory Machine Learning Through Convex Fairness Criteria. AAAI 2018: 3029-3036 - [c2]Naman Goel, Mohammad Yaghini, Boi Faltings:
Non-Discriminatory Machine Learning through Convex Fairness Criteria. AIES 2018: 116 - 2016
- [c1]Mehdi Naderi Soorki, Mohammad Yaghini, Mohammad Hossein Manshaei, Walid Saad, Hossein Saidi
:
Energy-aware optimization and mechanism design for cellular device-to-device local area networks. CISS 2016: 309-314 - [i1]Mehdi Naderi Soorki, Mohammad Yaghini, Mohammad Hossein Manshaei, Walid Saad, Hossein Saidi:
Energy-Aware Optimization and Mechanism Design for Cellular Device-to-Device Local Area Networks. CoRR abs/1601.06762 (2016)
Coauthor Index

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last updated on 2023-09-28 03:34 CEST by the dblp team
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