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08/23/2023
Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD
Differentially private SGD (DP-SGD) holds the promise of enabling the sa...
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11/18/2022
How Do Input Attributes Impact the Privacy Loss in Differential Privacy?
Differential privacy (DP) is typically formulated as a worst-case privac...
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10/07/2021
Complex-valued deep learning with differential privacy
We present ζ-DP, an extension of differential privacy (DP) to complex-va...
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09/22/2021
Partial sensitivity analysis in differential privacy
Differential privacy (DP) allows the quantification of privacy loss when...
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09/22/2021
An automatic differentiation system for the age of differential privacy
We introduce Tritium, an automatic differentiation-based sensitivity ana...
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09/22/2021
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index
The Gaussian mechanism (GM) represents a universally employed tool for a...
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07/30/2021
NeuralDP Differentially private neural networks by design
The application of differential privacy to the training of deep neural n...
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07/09/2021
Differentially private training of neural networks with Langevin dynamics for calibrated predictive uncertainty
We show that differentially private stochastic gradient descent (DP-SGD)...
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07/09/2021
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation
In recent years, formal methods of privacy protection such as differenti...
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07/06/2021
Differentially private federated deep learning for multi-site medical image segmentation
Collaborative machine learning techniques such as federated learning (FL...
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09/02/2020
