Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy

Anastasia Koloskova, Ryan McKenna, Zachary Charles +2

We study gradient descent under linearly correlated noise. Our work is motivated by recent practical methods for optimization with differential privacy (DP), such as DP-FTRL, which…