2 papers
stat.ML2025
Tracking the Median of Gradients with a Stochastic Proximal Point Method
Fabian Schaipp, Guillaume Garrigos, Umut Simsekli +1
There are several applications of stochastic optimization where one can benefit from a robust estimate of the gradient. For example, domains such as distributed learning with corru…
cs.LG2025
Analysis of an Idealized Stochastic Polyak Method and its Application to Black-Box Model Distillation
Robert M. Gower, Guillaume Garrigos, Nicolas Loizou +3
We provide a general convergence theorem of an idealized stochastic Polyak step size called SPS. Besides convexity, we only assume a local expected gradient bound, that include…