@article{browder1965nonexpansive,
  title={Nonexpansive nonlinear operators in a Banach space},
  author={Browder, Felix E},
  journal={Proceedings of the National Academy of Sciences},
  volume={54},
  number={4},
  pages={1041--1044},
  year={1965},
  publisher={National Acad Sciences}
}

@book{facchinei2003finite,
  title={Finite-dimensional variational inequalities and complementarity problems},
  author={Facchinei, Francisco and Pang, Jong-Shi},
  year={2003},
  publisher={Springer}
}

@book{kinderlehrer2000introduction,
  title={An introduction to variational inequalities and their applications},
  author={Kinderlehrer, David and Stampacchia, Guido},
  year={2000},
  publisher={SIAM}
}

@article{stampacchia1964formes,
  title={Formes bilineaires coercitives sur les ensembles convexes},
  author={Stampacchia, Guido},
  journal={Comptes Rendus Hebdomadaires Des Seances De L Academie Des Sciences},
  volume={258},
  number={18},
  pages={4413},
  year={1964},
  publisher={GAUTHIER-VILLARS/EDITIONS ELSEVIER 23 RUE LINOIS, 75015 PARIS, FRANCE}
}

@article{nesterov2005smooth,
  title={Smooth minimization of non-smooth functions},
  author={Nesterov, Yu},
  journal={Mathematical programming},
  volume={103},
  pages={127--152},
  year={2005},
  publisher={Springer}
}

@article{nemirovski2004prox,
  title={Prox-method with rate of convergence O (1/t) for variational inequalities with Lipschitz continuous monotone operators and smooth convex-concave saddle point problems},
  author={Nemirovski, Arkadi},
  journal={SIAM Journal on Optimization},
  volume={15},
  number={1},
  pages={229--251},
  year={2004},
  publisher={SIAM}
}

@article{esser2010general,
  title={A general framework for a class of first order primal-dual algorithms for convex optimization in imaging science},
  author={Esser, Ernie and Zhang, Xiaoqun and Chan, Tony F},
  journal={SIAM Journal on Imaging Sciences},
  volume={3},
  number={4},
  pages={1015--1046},
  year={2010},
  publisher={SIAM}
}

@article{beznosikov2023smooth,
  title={Smooth monotone stochastic variational inequalities and saddle point problems: A survey},
  author={Beznosikov, Aleksandr and Polyak, Boris and Gorbunov, Eduard and Kovalev, Dmitry and Gasnikov, Alexander},
  journal={European Mathematical Society Magazine},
  number={127},
  pages={15--28},
  year={2023}
}

@article{gidel2018variational,
  title={A variational inequality perspective on generative adversarial networks},
  author={Gidel, Gauthier and Berard, Hugo and Vignoud, Ga{\"e}tan and Vincent, Pascal and Lacoste-Julien, Simon},
  journal={arXiv preprint arXiv:1802.10551},
  year={2018}
}

@article{gemp2018global,
  title={Global convergence to the equilibrium of gans using variational inequalities},
  author={Gemp, Ian and Mahadevan, Sridhar},
  journal={arXiv preprint arXiv:1808.01531},
  year={2018}
}

@article{mertikopoulos2018optimistic,
  title={Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile},
  author={Mertikopoulos, Panayotis and Lecouat, Bruno and Zenati, Houssam and Foo, Chuan-Sheng and Chandrasekhar, Vijay and Piliouras, Georgios},
  journal={arXiv preprint arXiv:1807.02629},
  year={2018}
}

@article{korpelevich1976extragradient,
  title={The extragradient method for finding saddle points and other problems},
  author={Korpelevich, Galina M},
  journal={Matecon},
  volume={12},
  pages={747--756},
  year={1976}
}

@article{tseng2000modified,
  title={A modified forward-backward splitting method for maximal monotone mappings},
  author={Tseng, Paul},
  journal={SIAM Journal on Control and Optimization},
  volume={38},
  number={2},
  pages={431--446},
  year={2000},
  publisher={SIAM}
}

@article{carmon2019variance,
  title={Variance reduction for matrix games},
  author={Carmon, Yair and Jin, Yujia and Sidford, Aaron and Tian, Kevin},
  journal={Advances in Neural Information Processing Systems},
  volume={32},
  year={2019}
}

@article{chambolle2011first,
  title={A first-order primal-dual algorithm for convex problems with applications to imaging},
  author={Chambolle, Antonin and Pock, Thomas},
  journal={Journal of mathematical imaging and vision},
  volume={40},
  pages={120--145},
  year={2011},
  publisher={Springer}
}

@article{robbins1951stochastic,
  title={A stochastic approximation method},
  author={Robbins, Herbert and Monro, Sutton},
  journal={The annals of mathematical statistics},
  pages={400--407},
  year={1951},
  publisher={JSTOR}
}

@inproceedings{bottou2009curiously,
  title={Curiously fast convergence of some stochastic gradient descent algorithms},
  author={Bottou, L{\'e}on},
  booktitle={Proceedings of the symposium on learning and data science, Paris},
  volume={8},
  pages={2624--2633},
  year={2009},
  organization={Citeseer}
}

@article{moulines2011non,
  title={Non-asymptotic analysis of stochastic approximation algorithms for machine learning},
  author={Moulines, Eric and Bach, Francis},
  journal={Advances in neural information processing systems},
  volume={24},
  year={2011}
}

@book{lan2020first,
  title={First-order and stochastic optimization methods for machine learning},
  author={Lan, Guanghui},
  volume={1},
  year={2020},
  publisher={Springer}
}

@article{gower2020variance,
  title={Variance-reduced methods for machine learning},
  author={Gower, Robert M and Schmidt, Mark and Bach, Francis and Richt{\'a}rik, Peter},
  journal={Proceedings of the IEEE},
  volume={108},
  number={11},
  pages={1968--1983},
  year={2020},
  publisher={IEEE}
}

@article{johnson2013accelerating,
  title={Accelerating stochastic gradient descent using predictive variance reduction},
  author={Johnson, Rie and Zhang, Tong},
  journal={Advances in neural information processing systems},
  volume={26},
  year={2013}
}

@inproceedings{kovalev2020don,
  title={Don’t jump through hoops and remove those loops: SVRG and Katyusha are better without the outer loop},
  author={Kovalev, Dmitry and Horv{\'a}th, Samuel and Richt{\'a}rik, Peter},
  booktitle={Algorithmic Learning Theory},
  pages={451--467},
  year={2020},
  organization={PMLR}
}

@inproceedings{safran2020good,
  title={How good is SGD with random shuffling?},
  author={Safran, Itay and Shamir, Ohad},
  booktitle={Conference on Learning Theory},
  pages={3250--3284},
  year={2020},
  organization={PMLR}
}

@article{mishchenko2020random,
  title={Random reshuffling: Simple analysis with vast improvements},
  author={Mishchenko, Konstantin and Khaled, Ahmed and Richt{\'a}rik, Peter},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={17309--17320},
  year={2020}
}

@inproceedings{malinovsky2023random,
  title={Random reshuffling with variance reduction: New analysis and better rates},
  author={Malinovsky, Grigory and Sailanbayev, Alibek and Richt{\'a}rik, Peter},
  booktitle={Uncertainty in Artificial Intelligence},
  pages={1347--1357},
  year={2023},
  organization={PMLR}
}

@misc{koloskova2024convergence,
      title={On Convergence of Incremental Gradient for Non-Convex Smooth Functions}, 
      author={Anastasia Koloskova and Nikita Doikov and Sebastian U. Stich and Martin Jaggi},
      year={2024},
      eprint={2305.19259},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@article{roux2012stochastic,
  title={A stochastic gradient method with an exponential convergence \_rate for finite training sets},
  author={Roux, Nicolas and Schmidt, Mark and Bach, Francis},
  journal={Advances in neural information processing systems},
  volume={25},
  year={2012}
}

@article{defazio2014saga,
  title={SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives},
  author={Defazio, Aaron and Bach, Francis and Lacoste-Julien, Simon},
  journal={Advances in neural information processing systems},
  volume={27},
  year={2014}
}

@inproceedings{defazio2014finito,
  title={Finito: A faster, permutable incremental gradient method for big data problems},
  author={Defazio, Aaron and Domke, Justin and others},
  booktitle={International Conference on Machine Learning},
  pages={1125--1133},
  year={2014},
  organization={PMLR}
}

@inproceedings{nguyen2017sarah,
  title={SARAH: A novel method for machine learning problems using stochastic recursive gradient},
  author={Nguyen, Lam M and Liu, Jie and Scheinberg, Katya and Tak{\'a}{\v{c}}, Martin},
  booktitle={International conference on machine learning},
  pages={2613--2621},
  year={2017},
  organization={PMLR}
}

@article{hu2019efficient,
  title={Efficient smooth non-convex stochastic compositional optimization via stochastic recursive gradient descent},
  author={Hu, Wenqing and Li, Chris Junchi and Lian, Xiangru and Liu, Ji and Yuan, Huizhuo},
  journal={Advances in Neural Information Processing Systems},
  volume={32},
  year={2019}
}

@article{fang2018spider,
  title={Spider: Near-optimal non-convex optimization via stochastic path-integrated differential estimator},
  author={Fang, Cong and Li, Chris Junchi and Lin, Zhouchen and Zhang, Tong},
  journal={Advances in neural information processing systems},
  volume={31},
  year={2018}
}

@article{nesterov2007dual,
  title={Dual extrapolation and its applications to solving variational inequalities and related problems},
  author={Nesterov, Yurii},
  journal={Mathematical Programming},
  volume={109},
  number={2},
  pages={319--344},
  year={2007},
  publisher={Springer}
}

@article{malitsky2015projected,
  title={Projected reflected gradient methods for monotone variational inequalities},
  author={Malitsky, Yu},
  journal={SIAM Journal on Optimization},
  volume={25},
  number={1},
  pages={502--520},
  year={2015},
  publisher={SIAM}
}

@article{malitsky2020forward,
  title={A forward-backward splitting method for monotone inclusions without cocoercivity},
  author={Malitsky, Yura and Tam, Matthew K},
  journal={SIAM Journal on Optimization},
  volume={30},
  number={2},
  pages={1451--1472},
  year={2020},
  publisher={SIAM}
}

@article{palaniappan2016stochastic,
  title={Stochastic variance reduction methods for saddle-point problems},
  author={Palaniappan, Balamurugan and Bach, Francis},
  journal={Advances in Neural Information Processing Systems},
  volume={29},
  year={2016}
}

@article{chavdarova2019reducing,
  title={Reducing noise in GAN training with variance reduced extragradient},
  author={Chavdarova, Tatjana and Gidel, Gauthier and Fleuret, Fran{\c{c}}ois and Lacoste-Julien, Simon},
  journal={Advances in Neural Information Processing Systems},
  volume={32},
  year={2019}
}

@inproceedings{alacaoglu2022stochastic,
  title={Stochastic variance reduction for variational inequality methods},
  author={Alacaoglu, Ahmet and Malitsky, Yura},
  booktitle={Conference on Learning Theory},
  pages={778--816},
  year={2022},
  organization={PMLR}
}

@article{nguyen2021unified,
  title={A unified convergence analysis for shuffling-type gradient methods},
  author={Nguyen, Lam M and Tran-Dinh, Quoc and Phan, Dzung T and Nguyen, Phuong Ha and Van Dijk, Marten},
  journal={Journal of Machine Learning Research},
  volume={22},
  number={207},
  pages={1--44},
  year={2021}
}

@article{huang2021improved,
  title={An improved analysis and rates for variance reduction under without-replacement sampling orders},
  author={Huang, Xinmeng and Yuan, Kun and Mao, Xianghui and Yin, Wotao},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={3232--3243},
  year={2021}
}

@article{alacaoglu2021forward,
  title={Forward-reflected-backward method with variance reduction},
  author={Alacaoglu, Ahmet and Malitsky, Yura and Cevher, Volkan},
  journal={Computational optimization and applications},
  volume={80},
  number={2},
  pages={321--346},
  year={2021},
  publisher={Springer}
}

@article{stich2019unified,
  title={Unified optimal analysis of the (stochastic) gradient method},
  author={Stich, Sebastian U},
  journal={arXiv preprint arXiv:1907.04232},
  year={2019}
}

@article{chang2011libsvm,
  title={LIBSVM: a library for support vector machines},
  author={Chang, Chih-Chung and Lin, Chih-Jen},
  journal={ACM transactions on intelligent systems and technology (TIST)},
  volume={2},
  number={3},
  pages={1--27},
  year={2011},
  publisher={Acm New York, NY, USA}
}

@inproceedings{omidshafiei2017deep,
  title={Deep decentralized multi-task multi-agent reinforcement learning under partial observability},
  author={Omidshafiei, Shayegan and Pazis, Jason and Amato, Christopher and How, Jonathan P and Vian, John},
  booktitle={International Conference on Machine Learning},
  pages={2681--2690},
  year={2017},
  organization={PMLR}
}

@inproceedings{jin2020efficiently,
  title={Efficiently solving MDPs with stochastic mirror descent},
  author={Jin, Yujia and Sidford, Aaron},
  booktitle={International Conference on Machine Learning},
  pages={4890--4900},
  year={2020},
  organization={PMLR}
}

@article{madry2017towards,
  title={Towards deep learning models resistant to adversarial attacks},
  author={Madry, Aleksander and Makelov, Aleksandar and Schmidt, Ludwig and Tsipras, Dimitris and Vladu, Adrian},
  journal={arXiv preprint arXiv:1706.06083},
  year={2017}
}

@article{goodfellow2014generative,
  title={Generative adversarial nets},
  author={Goodfellow, Ian and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
  journal={Advances in neural information processing systems},
  volume={27},
  year={2014}
}

@article{daskalakis2017training,
  title={Training gans with optimism},
  author={Daskalakis, Constantinos and Ilyas, Andrew and Syrgkanis, Vasilis and Zeng, Haoyang},
  journal={arXiv preprint arXiv:1711.00141},
  year={2017}
}

@inproceedings{liang2019interaction,
  title={Interaction matters: A note on non-asymptotic local convergence of generative adversarial networks},
  author={Liang, Tengyuan and Stokes, James},
  booktitle={The 22nd International Conference on Artificial Intelligence and Statistics},
  pages={907--915},
  year={2019},
  organization={PMLR}
}

@article{peng2020training,
  title={Training GANs with centripetal acceleration},
  author={Peng, Wei and Dai, Yu-Hong and Zhang, Hui and Cheng, Lizhi},
  journal={Optimization Methods and Software},
  volume={35},
  number={5},
  pages={955--973},
  year={2020},
  publisher={Taylor \& Francis}
}

@book{von1953theory,
  title={Theory of games and economic behavior: by J. Von Neumann and O. Morgenstern},
  author={Von Neumann, John and Morgenstern, Oskar},
  year={1953},
  publisher={Princeton university press}
}

@article{xu2004maximum,
  title={Maximum margin clustering},
  author={Xu, Linli and Neufeld, James and Larson, Bryce and Schuurmans, Dale},
  journal={Advances in neural information processing systems},
  volume={17},
  year={2004}
}

@article{bach2008convex,
  title={Convex sparse matrix factorizations},
  author={Bach, Francis and Mairal, Julien and Ponce, Jean},
  journal={arXiv preprint arXiv:0812.1869},
  year={2008}
}

@book{ben2009robust,
  title={Robust optimization},
  author={Ben-Tal, Aharon and El Ghaoui, Laurent and Nemirovski, Arkadi},
  volume={28},
  year={2009},
  publisher={Princeton university press}
}

@inproceedings{medyakov2023optimal,
  title={Optimal data splitting in distributed optimization for machine learning},
  author={Medyakov, Daniil and Molodtsov, Gleb and Beznosikov, Aleksandr and Gasnikov, Alexander},
  booktitle={Doklady Mathematics},
  volume={108},
  number={Suppl 2},
  pages={S465--S475},
  year={2023},
  organization={Springer}
}

@article{harker1990finite,
  title={Finite-dimensional variational inequality and nonlinear complementarity problems: a survey of theory, algorithms and applications},
  author={Harker, Patrick T and Pang, Jong-Shi},
  journal={Mathematical programming},
  volume={48},
  number={1},
  pages={161--220},
  year={1990},
  publisher={Springer}
}

@inproceedings{bottou2010large,
  title={Large-scale machine learning with stochastic gradient descent},
  author={Bottou, L{\'e}on},
  booktitle={Proceedings of COMPSTAT'2010: 19th International Conference on Computational StatisticsParis France, August 22-27, 2010 Keynote, Invited and Contributed Papers},
  pages={177--186},
  year={2010},
  organization={Springer}
}

@article{dean2012large,
  title={Large scale distributed deep networks},
  author={Dean, Jeffrey and Corrado, Greg and Monga, Rajat and Chen, Kai and Devin, Matthieu and Mao, Mark and Ranzato, Marc'aurelio and Senior, Andrew and Tucker, Paul and Yang, Ke and others},
  journal={Advances in neural information processing systems},
  volume={25},
  year={2012}
}

@article{nemirovski2009robust,
  title={Robust stochastic approximation approach to stochastic programming},
  author={Nemirovski, Arkadi and Juditsky, Anatoli and Lan, Guanghui and Shapiro, Alexander},
  journal={SIAM Journal on optimization},
  volume={19},
  number={4},
  pages={1574--1609},
  year={2009},
  publisher={SIAM}
}

@article{polyak1992acceleration,
  title={Acceleration of stochastic approximation by averaging},
  author={Polyak, Boris T and Juditsky, Anatoli B},
  journal={SIAM journal on control and optimization},
  volume={30},
  number={4},
  pages={838--855},
  year={1992},
  publisher={SIAM}
}

@article{juditsky2011solving,
  title={Solving variational inequalities with stochastic mirror-prox algorithm},
  author={Juditsky, Anatoli and Nemirovski, Arkadi and Tauvel, Claire},
  journal={Stochastic Systems},
  volume={1},
  number={1},
  pages={17--58},
  year={2011},
  publisher={INFORMS}
}

@article{gurbuzbalaban2021random,
  title={Why random reshuffling beats stochastic gradient descent},
  author={G{\"u}rb{\"u}zbalaban, Mert and Ozdaglar, Asu and Parrilo, Pablo A},
  journal={Mathematical Programming},
  volume={186},
  pages={49--84},
  year={2021},
  publisher={Springer}
}

@inproceedings{haochen2019random,
  title={Random shuffling beats SGD after finite epochs},
  author={Haochen, Jeff and Sra, Suvrit},
  booktitle={International Conference on Machine Learning},
  pages={2624--2633},
  year={2019},
  organization={PMLR}
}

@inproceedings{nagaraj2019sgd,
  title={Sgd without replacement: Sharper rates for general smooth convex functions},
  author={Nagaraj, Dheeraj and Jain, Prateek and Netrapalli, Praneeth},
  booktitle={International Conference on Machine Learning},
  pages={4703--4711},
  year={2019},
  organization={PMLR}
}

@inproceedings{rajput2020closing,
  title={Closing the convergence gap of SGD without replacement},
  author={Rajput, Shashank and Gupta, Anant and Papailiopoulos, Dimitris},
  booktitle={International Conference on Machine Learning},
  pages={7964--7973},
  year={2020},
  organization={PMLR}
}

@techreport{mangasarian1993serial,
  title={Serial and Parallel Backpropagation Convergence Via Nonmonotone Perturbed Minimization},
  author={Mangasarian, Olvi L and Solodov, MV},
  year={1993},
  institution={University of Wisconsin-Madison Department of Computer Sciences}
}

@article{bertsekas2000gradient,
  title={Gradient convergence in gradient methods with errors},
  author={Bertsekas, Dimitri P and Tsitsiklis, John N},
  journal={SIAM Journal on Optimization},
  volume={10},
  number={3},
  pages={627--642},
  year={2000},
  publisher={SIAM}
}

@article{nedic2001incremental,
  title={Incremental subgradient methods for nondifferentiable optimization},
  author={Nedic, Angelia and Bertsekas, Dimitri P},
  journal={SIAM Journal on Optimization},
  volume={12},
  number={1},
  pages={109--138},
  year={2001},
  publisher={SIAM}
}

@article{li2019incremental,
  title={Incremental methods for weakly convex optimization},
  author={Li, Xiao and Zhu, Zhihui and So, Anthony Man-Cho and Lee, Jason D},
  journal={arXiv preprint arXiv:1907.11687},
  year={2019}
}

@inproceedings{allen2016improved,
  title={Improved SVRG for non-strongly-convex or sum-of-non-convex objectives},
  author={Allen-Zhu, Zeyuan and Yuan, Yang},
  booktitle={International conference on machine learning},
  pages={1080--1089},
  year={2016},
  organization={PMLR}
}

@article{mokhtari2018surpassing,
  title={Surpassing gradient descent provably: A cyclic incremental method with linear convergence rate},
  author={Mokhtari, Aryan and Gurbuzbalaban, Mert and Ribeiro, Alejandro},
  journal={SIAM Journal on Optimization},
  volume={28},
  number={2},
  pages={1420--1447},
  year={2018},
  publisher={SIAM}
}

@article{ying2020variance,
  title={Variance-reduced stochastic learning under random reshuffling},
  author={Ying, Bicheng and Yuan, Kun and Sayed, Ali H},
  journal={IEEE Transactions on Signal Processing},
  volume={68},
  pages={1390--1408},
  year={2020},
  publisher={IEEE}
}

@inproceedings{mishchenko2020revisiting,
  title={Revisiting stochastic extragradient},
  author={Mishchenko, Konstantin and Kovalev, Dmitry and Shulgin, Egor and Richt{\'a}rik, Peter and Malitsky, Yura},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={4573--4582},
  year={2020},
  organization={PMLR}
}

@inproceedings{mokhtari2020unified,
  title={A unified analysis of extra-gradient and optimistic gradient methods for saddle point problems: Proximal point approach},
  author={Mokhtari, Aryan and Ozdaglar, Asuman and Pattathil, Sarath},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={1497--1507},
  year={2020},
  organization={PMLR}
}

@article{beznosikov2020distributed,
  title={Distributed saddle-point problems: Lower bounds, near-optimal and robust algorithms},
  author={Beznosikov, Aleksandr and Samokhin, Valentin and Gasnikov, Alexander},
  journal={arXiv preprint arXiv:2010.13112},
  year={2020}
}

@article{schmidt2017minimizing,
  title={Minimizing finite sums with the stochastic average gradient},
  author={Schmidt, Mark and Le Roux, Nicolas and Bach, Francis},
  journal={Mathematical Programming},
  volume={162},
  number={1-2},
  pages={83--112},
  year={2017},
  publisher={Springer}
}

@inproceedings{qian2019saga,
  title={SAGA with arbitrary sampling},
  author={Qian, Xun and Qu, Zheng and Richt{\'a}rik, Peter},
  booktitle={International Conference on Machine Learning},
  pages={5190--5199},
  year={2019},
  organization={PMLR}
}

@inproceedings{li2021page,
  title={PAGE: A simple and optimal probabilistic gradient estimator for nonconvex optimization},
  author={Li, Zhize and Bao, Hongyan and Zhang, Xiangliang and Richt{\'a}rik, Peter},
  booktitle={International Conference on Machine Learning},
  pages={6286--6295},
  year={2021},
  organization={PMLR}
}

@article{cutkosky2019momentum,
  title={Momentum-based variance reduction in non-convex sgd},
  author={Cutkosky, Ashok and Orabona, Francesco},
  journal={arXiv preprint arXiv:1905.10018},
  year={2019}
}

@inproceedings{hsieh2019convergence,
 author = {Hsieh, Yu-Guan and Iutzeler, Franck and Malick, J\'{e}r\^{o}me and Mertikopoulos, Panayotis},
 booktitle = {Advances in Neural Information Processing Systems},
 pages = {6938--6948},
 publisher = {Curran Associates, Inc.},
 title = {On the convergence of single-call stochastic extra-gradient methods},
 volume = {32},
 year = {2019}
}

@inproceedings{hsieh2020explore,
  title={Explore aggressively, update conservatively: Stochastic extragradient methods with variable stepsize scaling},
  author={Hsieh, Yu-Guan and Iutzeler, Franck and Malick, J{\'e}r{\^o}me and Mertikopoulos, Panayotis},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={16223--16234},
  year={2020}
}

@inproceedings{gorbunov2022stochastic,
  title={Stochastic extragradient: General analysis and improved rates},
  author={Gorbunov, Eduard and Berard, Hugo and Gidel, Gauthier and Loizou, Nicolas},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={7865--7901},
  year={2022},
  organization={PMLR}
}

@article{beznosikov2024first,
  title={First order methods with markovian noise: from acceleration to variational inequalities},
  author={Beznosikov, Aleksandr and Samsonov, Sergey and Sheshukova, Marina and Gasnikov, Alexander and Naumov, Alexey and Moulines, Eric},
  journal={Advances in Neural Information Processing Systems},
  volume={36},
  year={2024}
}

@article{solodkin2024methods,
  title={Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry},
  author={Solodkin, Vladimir and Veprikov, Andrew and Beznosikov, Aleksandr},
  journal={arXiv preprint arXiv:2408.01848},
  year={2024}
}

@article{alacaoglu2021stochastic,
  title={Stochastic variance reduction for variational inequality methods},
  author={Alacaoglu, Ahmet and Malitsky, Yura},
  journal={arXiv preprint arXiv:2102.08352},
  year={2021}
}

@article{Yura2021,
author = {Alacaoglu, Ahmet and Malitsky, Yura and Cevher, Volkan},
year = {2021},
month = {11},
pages = {},
title = {Forward-reflected-backward method with variance reduction},
volume = {80},
journal = {Computational Optimization and Applications},
doi = {10.1007/s10589-021-00305-3}
}

@article{kovalev2022optimalvi,
  title={Optimal algorithms for decentralized stochastic variational inequalities},
  author={Kovalev, Dmitry and Beznosikov, Aleksandr and Sadiev, Abdurakhmon and Persiianov, Michael and Richt{\'a}rik, Peter and Gasnikov, Alexander},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={31073--31088},
  year={2022}
}


@article{pichugin2024method,
  title={Method with batching for stochastic finite-sum variational inequalities in non-Euclidean setting},
  author={Pichugin, Alexander and Pechin, Maksim and Beznosikov, Aleksandr and Novitskii, Vasilii and Gasnikov, Alexander},
  journal={Chaos, Solitons \& Fractals},
  volume={187},
  pages={115396},
  year={2024},
  publisher={Elsevier}
}

@inproceedings{pichugin2023optimal,
  title={Optimal analysis of method with batching for monotone stochastic finite-sum variational inequalities},
  author={Pichugin, Alexander and Pechin, Maksim and Beznosikov, Aleksandr and Savchenko, A and Gasnikov, A},
  booktitle={Doklady Mathematics},
  volume={108},
  number={Suppl 2},
  pages={S348--S359},
  year={2023},
  organization={Springer}
}

@article{beznosikov2022unified,
  title={A Unified Analysis of Variational Inequality Methods: Variance Reduction, Sampling, Quantization andCoordinate Descent},
  author={Beznosikov, A. and Gasnikov, A. and Zainulina, K. and Maslovskiy, A. and Pasechnyuk, D.},
  journal={arXiv preprint arXiv:2201.12206},
  year={2022}
}

@inproceedings{medyakovshuffling,
  title={Shuffling Heuristic in Variational Inequalities: Establishing New Convergence Guarantees},
  author={Medyakov, Daniil and Molodtsov, Gleb and Grigoriy, Evseev and Petrov, Egor and Beznosikov, Aleksandr},
  booktitle={International Conference on Computational Optimization},
  year={2024}
}

@article{chen2022faster,
  title={Faster stochastic algorithms for minimax optimization under polyak-$\{$$\backslash$L$\}$ ojasiewicz condition},
  author={Chen, Lesi and Yao, Boyuan and Luo, Luo},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={13921--13932},
  year={2022}
}

@incollection{beznosikov2023sarah,
  title={Sarah-based variance-reduced algorithm for stochastic finite-sum cocoercive variational inequalities},
  author={Beznosikov, Aleksandr and Gasnikov, Alexander},
  booktitle={Data Analysis and Optimization: In Honor of Boris Mirkin's 80th Birthday},
  pages={47--57},
  year={2023},
  publisher={Springer}
}

@article{loizou2021stochastic,
  title={Stochastic gradient descent-ascent and consensus optimization for smooth games: Convergence analysis under expected co-coercivity},
  author={Loizou, Nicolas and Berard, Hugo and Gidel, Gauthier and Mitliagkas, Ioannis and Lacoste-Julien, Simon},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={19095--19108},
  year={2021}
}

@article{krizhevsky2009learning,
  title={Learning multiple layers of features from tiny images},
  author={Krizhevsky, Alex and Hinton, Geoffrey and others},
  year={2009},
  publisher={Toronto, ON, Canada}
}

@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={770--778},
  year={2016}
}

@article{cybenko1989approximation,
  title={Approximation by superpositions of a sigmoidal function},
  author={Cybenko, George},
  journal={Mathematics of control, signals and systems},
  volume={2},
  number={4},
  pages={303--314},
  year={1989},
  publisher={Springer}
}

@article{paszke2019pytorch,
  title={Pytorch: An imperative style, high-performance deep learning library},
  author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@article{karras2019style,
  title={A Style-Based Generator Architecture for Generative Adversarial Networks},
  author={Karras, Tero},
  journal={arXiv preprint arXiv:1812.04948},
  year={2019}
}