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Mohammad Yaghini

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Regulation Games for Trustworthy Machine Learning

Feb 05, 2024
Mohammad Yaghini, Patty Liu, Franziska Boenisch, Nicolas Papernot

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Learning with Impartiality to Walk on the Pareto Frontier of Fairness, Privacy, and Utility

Feb 17, 2023
Mohammad Yaghini, Patty Liu, Franziska Boenisch, Nicolas Papernot

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On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning

Aug 06, 2022
Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot

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$p$-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations

Jul 25, 2022
Adam Dziedzic, Stephan Rabanser, Mohammad Yaghini, Armin Ale, Murat A. Erdogdu, Nicolas Papernot

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Pipe Overflow: Smashing Voice Authentication for Fun and Profit

Feb 06, 2022
Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz

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SoK: Machine Learning Governance

Sep 20, 2021
Varun Chandrasekaran, Hengrui Jia, Anvith Thudi, Adelin Travers, Mohammad Yaghini, Nicolas Papernot

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Dataset Inference: Ownership Resolution in Machine Learning

Apr 21, 2021
Pratyush Maini, Mohammad Yaghini, Nicolas Papernot

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Proof-of-Learning: Definitions and Practice

Mar 09, 2021
Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot

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A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness

Nov 08, 2019
Mohammad Yaghini, Hoda Heidari, Andreas Krause

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Disparate Vulnerability: on the Unfairness of Privacy Attacks Against Machine Learning

Jun 02, 2019
Mohammad Yaghini, Bogdan Kulynych, Carmela Troncoso

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