| 2025 | AISTATS | Improving Stochastic Cubic Newton with Momentum. | El Mahdi Chayti, Nikita Doikov, Martin Jaggi |
| 2025 | AISTATS | Cubic regularized subspace Newton for non-convex optimization. | Jim Zhao, Nikita Doikov, Aurlien Lucchi |
| 2025 | ICML | On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists. | Dongyang Fan, Bettina Messmer, Nikita Doikov, Martin Jaggi |
| 2024 | ICML | Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions. | Nikita Doikov, Sebastian U. Stich, Martin Jaggi |
| 2024 | ICML | On Convergence of Incremental Gradient for Non-convex Smooth Functions. | Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi |
| 2023 | COLT | Linearization Algorithms for Fully Composite Optimization. | Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion |
| 2023 | ICML | Second-Order Optimization with Lazy Hessians. | Nikita Doikov, El Mahdi Chayti, Martin Jaggi |
| 2023 | ICML | Polynomial Preconditioning for Gradient Methods. | Nikita Doikov, Anton Rodomanov |
| 2020 | ICML | Inexact Tensor Methods with Dynamic Accuracies. | Nikita Doikov, Yurii E. Nesterov |
| 2020 | ICML | Stochastic Subspace Cubic Newton Method. | Filip Hanzely, Nikita Doikov, Yurii E. Nesterov, Peter Richtrik |
| 2018 | ICML | Randomized Block Cubic Newton Method. | Nikita Doikov, Peter Richtrik |