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Nicolas Loizou
Nicolas Loizou
Johns Hopkins University
Подтвержден адрес электронной почты в домене jhu.edu - Главная страница
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Процитировано
Процитировано
Год
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates
A Koloskova, N Loizou, S Boreiri, M Jaggi, SU Stich
ICML 2020 - Proceedings of the 37th International Conference on Machine Learning, 2020
3632020
SGD: General Analysis and Improved Rates
RM Gower, N Loizou, X Qian, A Sailanbayev, E Shulgin, P Richtarik
ICML 2019 - Proceedings of the 36th International Conference on Machine Learning, 2019
3532019
Stochastic gradient push for distributed deep learning
M Assran, N Loizou, N Ballas, M Rabbat
ICML 2019 - Proceedings of the 36th International Conference on Machine Learning, 2018
3362018
Momentum and stochastic momentum for stochastic gradient, Newton, proximal point and subspace descent methods
N Loizou, P Richtárik
Computational Optimization and Applications, 77 (3), 653-710, 2020
1912020
Stochastic Polyak step-size for SGD: An adaptive learning rate for fast convergence
N Loizou, S Vaswani, I Laradji, S Lacoste-Julien
AISTATS 2021 - International Conference on Artificial Intelligence and …, 2021
1212021
SGD for structured nonconvex functions: Learning rates, minibatching and interpolation
RM Gower, O Sebbouh, N Loizou
AISTATS 2021 - International Conference on Artificial Intelligence and …, 2021
652021
Extragradient method: O (1/K) last-iterate convergence for monotone variational inequalities and connections with cocoercivity
E Gorbunov, N Loizou, G Gidel
AISTATS 2022 - International Conference on Artificial Intelligence and …, 2022
592022
Stochastic Hamiltonian Gradient Methods for Smooth Games
N Loizou, H Berard, A Jolicoeur-Martineau, P Vincent, S Lacoste-Julien, ...
ICML 2020 - Proceedings of the 37th International Conference on Machine Learning, 2020
482020
Linearly convergent stochastic heavy ball method for minimizing generalization error
N Loizou, P Richtárik
NIPS 2017- Workshop on Optimization for Machine Learning , arXiv preprint …, 2017
422017
Unified analysis of stochastic gradient methods for composite convex and smooth optimization
A Khaled, O Sebbouh, N Loizou, RM Gower, P Richtárik
Journal of Optimization Theory and Applications, 1-42, 2023
372023
Stochastic gradient descent-ascent and consensus optimization for smooth games: Convergence analysis under expected co-coercivity
N Loizou, H Berard, G Gidel, I Mitliagkas, S Lacoste-Julien
NeurIPS 2021 - Advances in Neural Information Processing Systems, 2021
352021
Stochastic gradient descent-ascent: Unified theory and new efficient methods
A Beznosikov, E Gorbunov, H Berard, N Loizou
AISTATS 2023 - International Conference on Artificial Intelligence and …, 2023
322023
A new perspective on randomized gossip algorithms
N Loizou, P Richtárik
IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2016
322016
Revisiting Randomized Gossip Algorithms: General Framework, Convergence Rates and Novel Block and Accelerated Protocols
N Loizou, P Richtárik
IEEE Transactions on Information Theory 67 (12), 8300 - 8324, 2021
302021
Accelerated Gossip via Stochastic Heavy Ball Method
N Loizou, P Richtárik
56th Annual Allerton Conference on Communication, Control, and Computing, 2018, 2018
282018
Provably accelerated randomized gossip algorithms
N Loizou, M Rabbat, P Richtárik
ICASSP 2019 - IEEE International Conference on Acoustics, Speech and Signal …, 2018
262018
A unified approach to reinforcement learning, quantal response equilibria, and two-player zero-sum games
S Sokota, R D'Orazio, JZ Kolter, N Loizou, M Lanctot, I Mitliagkas, ...
ICLR 2023 - International Conference on Learning Representations, 2022
232022
Stochastic extragradient: General analysis and improved rates
E Gorbunov, H Berard, G Gidel, N Loizou
AISTATS 2022 - International Conference on Artificial Intelligence and …, 2022
232022
Convergence analysis of inexact randomized iterative methods
N Loizou, P Richtárik
SIAM Journal on Scientific Computing 42 (6), A3979-A4016, 2020
222020
Stochastic mirror descent: Convergence analysis and adaptive variants via the mirror stochastic Polyak stepsize
R D'Orazio, N Loizou, I Laradji, I Mitliagkas
Transactions on Machine Learning Research, 2021
212021
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