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02/17/2023
Learning with Impartiality to Walk on the Pareto Frontier of Fairness, Privacy, and Utility
Deploying machine learning (ML) models often requires both fairness and ...
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08/06/2022
On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning
Proof-of-learning (PoL) proposes a model owner use machine learning trai...
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07/25/2022
p-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations
The lack of well-calibrated confidence estimates makes neural networks i...
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02/06/2022
Pipe Overflow: Smashing Voice Authentication for Fun and Profit
Recent years have seen a surge of popularity of acoustics-enabled person...
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09/20/2021
SoK: Machine Learning Governance
The application of machine learning (ML) in computer systems introduces ...
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04/21/2021
Dataset Inference: Ownership Resolution in Machine Learning
With increasingly more data and computation involved in their training, ...
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03/09/2021
Proof-of-Learning: Definitions and Practice
Training machine learning (ML) models typically involves expensive itera...
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11/08/2019
A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness
Despite the recent surge of interest in designing and guaranteeing mathe...
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06/02/2019
