14 citations · 18 across the 4 of their papers we have counts for
5 papers
Optimizers for Diffusion Models: A Controlled Benchmark
Arman Bolatov, Egor Shulgin, David Li +6
Discrete diffusion models now match autoregressive language models on several benchmarks, while the question of how best to train them has received far less attention: the optimize…
Double Momentum and Error Feedback for Clipping with Fast Rates and Differential Privacy
Rustem Islamov, Samuel Horvath, Aurelien Lucchi +2
Strong Differential Privacy (DP) and Optimization guarantees are two desirable properties for a method in Federated Learning (FL). However, existing algorithms do not achieve both…
Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications
Antonin Chambolle, Matthias J. Ehrhardt, Peter Richtárik +1
We propose a stochastic extension of the primal-dual hybrid gradient algorithm studied by Chambolle and Pock in 2011 to solve saddle point problems that are separable in the dual v…
mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting
Jakub Konečný, Jie Liu, Peter Richtárik +1
We propose a mini-batching scheme for improving the theoretical complexity and practical performance of semi-stochastic gradient descent applied to the problem of minimizing a stro…
Matrix Completion under Interval Uncertainty
Jakub Marecek, Peter Richtarik, Martin Takac
Matrix completion under interval uncertainty can be cast as matrix completion with element-wise box constraints. We present an efficient alternating-direction parallel coordinate-d…