Nikita Doikov - RankMe

35 papers A* 10A 2Journal 22

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Cubic regularized subspace Newton for non-convex optimization. AISTATS Jim Zhao, Nikita Doikov, Aurélien Lucchi
2025	J	`jnl`	First and Zeroth-Order Implementations of the Regularized Newton Method with Lazy Approximated Hessians. J. Sci. Comput. Nikita Doikov, Geovani Nunes Grapiglia
2025	J	`jnl`	Gradient-Normalized Smoothness for Optimization with Approximate Hessians. CoRR Andrei Semenov, Martin Jaggi, Nikita Doikov
2025	A	`conf`	Improving Stochastic Cubic Newton with Momentum. AISTATS El Mahdi Chayti, Nikita Doikov, Martin Jaggi
2025	J	`jnl`	Lower complexity bounds for minimizing regularized functions. Optim. Lett. Nikita Doikov
2025	A*	`conf`	On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists. ICML Dongyang Fan, Bettina Messmer, Nikita Doikov, Martin Jaggi
2024	J	`jnl`	Cubic regularized subspace Newton for non-convex optimization. CoRR Jim Zhao, Aurélien Lucchi, Nikita Doikov
2024	J	`jnl`	Gradient regularization of Newton method with Bregman distances. Math. Program. Nikita Doikov, Yurii E. Nesterov
2024	J	`jnl`	Improving Stochastic Cubic Newton with Momentum. CoRR El Mahdi Chayti, Nikita Doikov, Martin Jaggi
2024	A*	`conf`	On Convergence of Incremental Gradient for Non-convex Smooth Functions. ICML Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi
2024	A*	`conf`	Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions. ICML Nikita Doikov, Sebastian U. Stich, Martin Jaggi
2024	J	`jnl`	Super-Universal Regularized Newton Method. SIAM J. Optim. Nikita Doikov, Konstantin Mishchenko, Yurii E. Nesterov
2024	J	`jnl`	Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods. Trans. Mach. Learn. Res. El Mahdi Chayti, Martin Jaggi, Nikita Doikov
2023	J	`jnl`	Affine-invariant contracting-point methods for Convex Optimization. Math. Program. Nikita Doikov, Yurii E. Nesterov
2023	J	`jnl`	First and zeroth-order implementations of the regularized Newton method with lazy approximated Hessians. CoRR Nikita Doikov, Geovani Nunes Grapiglia
2023	A*	`conf`	Linearization Algorithms for Fully Composite Optimization. COLT Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion
2023	J	`jnl`	Linearization Algorithms for Fully Composite Optimization. CoRR Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion
2023	J	`jnl`	Minimizing Quasi-Self-Concordant Functions by Gradient Regularization of Newton Method. CoRR Nikita Doikov
2023	A*	`conf`	Polynomial Preconditioning for Gradient Methods. ICML Nikita Doikov, Anton Rodomanov
2023	J	`jnl`	Polynomial Preconditioning for Gradient Methods. CoRR Nikita Doikov, Anton Rodomanov
2023	A*	`conf`	Second-Order Optimization with Lazy Hessians. ICML Nikita Doikov, El Mahdi Chayti, Martin Jaggi
2023	J	`jnl`	Shuffle SGD is Always Better than SGD: Improved Analysis of SGD with Arbitrary Data Orders. CoRR Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi
2023	J	`jnl`	Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods. CoRR El Mahdi Chayti, Nikita Doikov, Martin Jaggi
2022	J	`jnl`	High-Order Optimization Methods for Fully Composite Problems. SIAM J. Optim. Nikita Doikov, Yurii E. Nesterov
2022	J	`jnl`	Local convergence of tensor methods. Math. Program. Nikita Doikov, Yurii E. Nesterov
2022	J	`jnl`	Second-order optimization with lazy Hessians. CoRR Nikita Doikov, El Mahdi Chayti, Martin Jaggi
2022	J	`jnl`	Super-Universal Regularized Newton Method. CoRR Nikita Doikov, Konstantin Mishchenko, Yurii E. Nesterov
2021	J	`jnl`	Minimizing Uniformly Convex Functions by Cubic Regularization of Newton Method. J. Optim. Theory Appl. Nikita Doikov, Yurii E. Nesterov
2021	—	`—`	New second-order and tensor methods in convex optimization. Nikita Doikov
2020	J	`jnl`	Contracting Proximal Methods for Smooth Convex Optimization. SIAM J. Optim. Nikita Doikov, Yurii E. Nesterov
2020	A*	`conf`	Convex optimization based on global lower second-order models. NeurIPS Nikita Doikov, Yurii E. Nesterov
2020	A*	`conf`	Inexact Tensor Methods with Dynamic Accuracies. ICML Nikita Doikov, Yurii E. Nesterov
2020	A*	`conf`	Stochastic Subspace Cubic Newton Method. ICML Filip Hanzely, Nikita Doikov, Yurii E. Nesterov, Peter Richtárik
2020	J	`jnl`	Stochastic Subspace Cubic Newton Method. CoRR Filip Hanzely, Nikita Doikov, Peter Richtárik, Yurii E. Nesterov
2018	A*	`conf`	Randomized Block Cubic Newton Method. ICML Nikita Doikov, Peter Richtárik