21 citations · 136 across the 22 of their papers we have counts for
3 papers · 1 filter
The Relative Gaussian Mechanism and its Application to Private Gradient Descent
Hadrien Hendrikx, Paul Mangold, Aurélien Bellet
The Gaussian Mechanism (GM), which consists in adding Gaussian noise to a vector-valued query before releasing it, is a standard privacy protection mechanism. In particular, given…
Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees
Anastasia Koloskova, Hadrien Hendrikx, Sebastian U. Stich
Gradient clipping is a popular modification to standard (stochastic) gradient descent, at every iteration limiting the gradient norm to a certain value . It is widely used fo…
Beyond spectral gap (extended): The role of the topology in decentralized learning
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rat…