2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Understanding Progressive Training Through the Framework of Randomized Coordinate Descent
Rafał Szlendak, Elnur Gasanov, Peter Richtárik
We propose a Randomized Progressive Training algorithm (RPT) -- a stochastic proxy for the well-known Progressive Training method (PT) (Karras et al., 2017). Originally designed to…
cs.LG2021★ 2 cited
Permutation Compressors for Provably Faster Distributed Nonconvex Optimization
Rafał Szlendak, Alexander Tyurin, Peter Richtárik
We study the MARINA method of Gorbunov et al (2021) -- the current state-of-the-art distributed non-convex optimization method in terms of theoretical communication complexity. The…