Doikov, Nikita

14 publications

AISTATS 2025 Cubic Regularized Subspace Newton for Non-Convex Optimization Jim Zhao, Nikita Doikov, Aurelien Lucchi

AISTATS 2025 Improving Stochastic Cubic Newton with Momentum El Mahdi Chayti, Nikita Doikov, Martin Jaggi

ICML 2025 On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists Dongyang Fan, Bettina Messmer, Nikita Doikov, Martin Jaggi

ICLRW 2025 On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists Dongyang Fan, Bettina Messmer, Nikita Doikov, Martin Jaggi

ICML 2024 On Convergence of Incremental Gradient for Non-Convex Smooth Functions Anastasia Koloskova, Nikita Doikov, Sebastian U Stich, Martin Jaggi

ICML 2024 Spectral Preconditioning for Gradient Methods on Graded Non-Convex Functions Nikita Doikov, Sebastian U Stich, Martin Jaggi

TMLR 2024 Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods El Mahdi Chayti, Martin Jaggi, Nikita Doikov

COLT 2023 Linearization Algorithms for Fully Composite Optimization Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion

ICML 2023 Polynomial Preconditioning for Gradient Methods Nikita Doikov, Anton Rodomanov

ICML 2023 Second-Order Optimization with Lazy Hessians Nikita Doikov, El Mahdi Chayti, Martin Jaggi

NeurIPS 2020 Convex Optimization Based on Global Lower Second-Order Models Nikita Doikov, Yurii Nesterov

ICML 2020 Inexact Tensor Methods with Dynamic Accuracies Nikita Doikov, Yurii Nesterov

ICML 2020 Stochastic Subspace Cubic Newton Method Filip Hanzely, Nikita Doikov, Yurii Nesterov, Peter Richtarik

ICML 2018 Randomized Block Cubic Newton Method Nikita Doikov, Peter Richtarik, University Edinburgh