Author

Yuriy Dorn

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Preprint Sep 2026

Lower Bounds For Gradient-Free Convex Optimization And Convex-Concave Saddle-Point Problems

We study the query complexity of optimization with exact scalar-value information. For globally $L$-smooth convex functions on $\mathbb R^d$ with a minimizer in a Euclidean ball of radius $R$, we prove the lower bound $\Omega(d\min\{d,\sqrt{LR^2/\varepsilon}\})$ for adaptive randomized algorithms in the stated accuracy...

Yuriy Dorn, D. Dvinskikh, Т. В. Логінов et al. · 0 citations

Preprint Sep 2026

Smooth or Separable? Sparse Block Acceleration for Entropy-Regularized Linear Programs

We study entropy-regularized linear programs with sparse affine constraints and compare two exact dual representations induced by whether a redundant normalization constraint is retained or eliminated. Eliminating it yields a partially separable sum-exp dual with sparse affine factors but unbounded curvature. Our main...

I. Podlipnova, Maxim Mashtaler, A. Agafonov et al. · 0 citations

Preprint Sep 2026

The Complexity of Convex Optimization with Mismatched Geometry

Optimal first-order methods on non-Euclidean domains such as the $\ell_1$ ball $B_1^n(R)=\{x\in\mathbb R^n:\|x\|_1\le R\}$ pair the prox-function with the norm in which smoothness is measured. When the gradient is $L$-Lipschitz in the Euclidean norm only, the accelerated method with a Euclidean prox-setup reduces the f...

Т. В. Логінов, A. Gasnikov, Yuriy Dorn et al. · 0 citations