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Anton Rodomanov
Anton Rodomanov
CISPA Helmholtz Center for Information Security
Geverifieerd e-mailadres voor cispa.de
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Greedy quasi-Newton methods with explicit superlinear convergence
A Rodomanov, Y Nesterov
SIAM Journal on Optimization 31 (1), 785-811, 2021
582021
Rates of superlinear convergence for classical quasi-Newton methods
A Rodomanov, Y Nesterov
Mathematical Programming, 1-32, 2022
562022
Putting MRFs on a tensor train
A Novikov, A Rodomanov, A Osokin, D Vetrov
International Conference on Machine Learning, 811-819, 2014
542014
New Results on Superlinear Convergence of Classical Quasi-Newton Methods
A Rodomanov, Y Nesterov
Journal of Optimization Theory and Applications 188, 744-769, 2021
532021
A superlinearly-convergent proximal Newton-type method for the optimization of finite sums
A Rodomanov, D Kropotov
International Conference on Machine Learning, 2597-2605, 2016
472016
Primal-dual method for searching equilibrium in hierarchical congestion population games
P Dvurechensky, A Gasnikov, E Gasnikova, S Matsievsky, A Rodomanov, ...
arXiv preprint arXiv:1606.08988, 2016
362016
A randomized coordinate descent method with volume sampling
A Rodomanov, D Kropotov
SIAM Journal on Optimization 30 (3), 1878-1904, 2020
132020
Smoothness parameter of power of Euclidean norm
A Rodomanov, Y Nesterov
Journal of Optimization Theory and Applications 185, 303-326, 2020
82020
Subgradient ellipsoid method for nonsmooth convex problems
A Rodomanov, Y Nesterov
Mathematical Programming 199 (1), 305-341, 2023
32023
Quasi-Newton Methods with Provable Efficiency Guarantees
A Rodomanov
PhD thesis, UCL-Université Catholique de Louvain, 2022
22022
Polynomial preconditioning for gradient methods
N Doikov, A Rodomanov
International Conference on Machine Learning, 8162-8187, 2023
12023
Global Complexity Analysis of BFGS
A Rodomanov
arXiv preprint arXiv:2404.15051, 2024
2024
Federated Optimization with Doubly Regularized Drift Correction
X Jiang, A Rodomanov, SU Stich
arXiv preprint arXiv:2404.08447, 2024
2024
Non-Convex Stochastic Composite Optimization with Polyak Momentum
Y Gao, A Rodomanov, SU Stich
arXiv preprint arXiv:2403.02967, 2024
2024
Universal Gradient Methods for Stochastic Convex Optimization
A Rodomanov, A Kavis, Y Wu, K Antonakopoulos, V Cevher
arXiv preprint arXiv:2402.03210, 2024
2024
Gradient Methods for Stochastic Optimization in Relative Scale
Y Nesterov, A Rodomanov
arXiv preprint arXiv:2301.08352, 2023
2023
Linear Coupling of Gradient and Mirror Descent: Version for Composite Functions with Adaptive Estimation of the Lipschitz Constant
A Rodomanov
2016
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Artikelen 1–17