most citedDifferentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

cs.LG2025

Learning to Forget with Information Divergence Reweighted Objectives for Noisy Labels

Jeremiah Birrell, Reza Ebrahimi

We introduce ANTIDOTE, a new class of objectives for learning under noisy labels which are defined in terms of a relaxation over an information-divergence neighborhood. Using conve…

cs.LG2024★ 1 cited

Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement

Jeremiah Birrell, Reza Ebrahimi, Rouzbeh Behnia +1

Differentially private stochastic gradient descent (DP-SGD) has been instrumental in privately training deep learning models by providing a framework to control and track the priva…