Graph-based Nearest Neighbor Search in Hyperbolic Spaces. - Liudmila Prokhorenkova; Dmitry Baranchuk; Nikolay Bogachev; Yury Demidovich; Alexander Kolpakov (ICLR, 2022)

A Guide Through the Zoo of Biased SGD. - Yury Demidovich; Grigory Malinovsky; Igor Sokolov 001; Peter Richtárik (NeurIPS, 2023)

Reconstruction of colours. - Yury Demidovich; Yaroslav Panichkin; Maksim Zhukovskii (CoRR, 2023)

Tight asymptotics of clique-chromatic numbers of dense random graphs. - Yury Demidovich; Maksim Zhukovskii (J. Graph Theory, 2023)

Cycle Saturation in Random Graphs. - Yury Demidovich; Arkadiy Skorkin; Maksim Zhukovskii (SIAM J. Discret. Math., 2023)

Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction. - Yury Demidovich; Grigory Malinovsky; Peter Richtárik (CoRR, 2024)

A Unified Theory of Stochastic Proximal Point Methods without Smoothness. - Peter Richtárik; Abdurakhmon Sadiev; Yury Demidovich (CoRR, 2024)

MAST: model-agnostic sparsified training. - Yury Demidovich; Grigory Malinovsky; Egor Shulgin; Peter Richtárik (ICLR, 2025)

Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization. - Yury Demidovich; Petr Ostroukhov; Grigory Malinovsky; Samuel Horváth; Martin Takác 001; Peter Richtárik; Eduard Gorbunov (ICLR, 2025)

Correlated Quantization for Faster Nonconvex Distributed Optimization. - Andrei Panferov; Yury Demidovich; Ahmad Rammal; Peter Richtárik (UAI, 2025)

Bernoulli-LoRA: A Theoretical Framework for Randomized Low-Rank Adaptation. - Igor Sokolov 001; Abdurakhmon Sadiev; Yury Demidovich; Fawaz S. Al-Qahtani; Peter Richtárik (CoRR, 2025)