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07/01/2023
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD
Differentially private stochastic gradient descent (DP-SGD) is the canon...
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05/28/2023
Training Private Models That Know What They Don't Know
Training reliable deep learning models which avoid making overconfident ...
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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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05/26/2022
Selective Classification Via Neural Network Training Dynamics
Selective classification is the task of rejecting inputs a model would p...
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02/24/2022
Bounding Membership Inference
Differential Privacy (DP) is the de facto standard for reasoning about t...
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10/22/2021
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning
Machine unlearning, i.e. having a model forget about some of its trainin...
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09/27/2021
Unrolling SGD: Understanding Factors Influencing Machine Unlearning
Machine unlearning is the process through which a deployed machine learn...
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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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03/09/2021
