3 citations · 10 across the 14 of their papers we have counts for
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Optimal Parameter-Free Second-order Acceleration with Inexact Hessians under Generalized Smoothness
Artem Agafonov, Aslan Ashabokov, Alexander D'yakonov +3
We study second-order convex optimization under generalized Hessian smoothness, where the local Hessian Lipschitz constant may grow linearly with the gradient norm. For inexact Hes…
Clipped or Unclipped? Finite-Sample Trade-offs for Averaged SGD under Heavy-Tailed Noise
Alexandra Suvorikova, Egor Gladin, Darina Dvinskikh +5
Gradient clipping is widely used to stabilize training, but it need not improve the statistical accuracy of averaged SGD, even under heavy-tailed noise. We derive a finite-sample c…
Smooth or Separable? Sparse Block Acceleration for Entropy-Regularized Linear Programs
Irina Podlipnova, Maxim Mashtaler, Artem Agafonov +2
We study entropy-regularized linear programs with sparse affine constraints and compare two exact dual representations induced by whether a redundant normalization constraint is re…
Application of Optimal Inexact Second-Order Acceleration to Distributed Stochastic Optimization under Statistical Similarity
Yury A. Sokolov, Maxim K. Mashtaler, Alexander V. Gasnikov +3
We consider distributed stochastic convex optimization with a fixed budget of independent samples split among workers. Sample average approximation reduces the problem to a…