1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent
Lauren Watson, Eric Gan, Mohan Dantam +2
Differentially private stochastic gradient descent (DP-SGD) is known to have poorer training and test performance on large neural networks, compared to ordinary stochastic gradient…
cs.LG2023★ 1 cited
Accelerated Shapley Value Approximation for Data Evaluation
Lauren Watson, Zeno Kujawa, Rayna Andreeva +3
Data valuation has found various applications in machine learning, such as data filtering, efficient learning and incentives for data sharing. The most popular current approach to…