1. Basu, D., Data, D., Karakus, C., Diggavi, S.: Qsparse-local-sgd: distributed sgd with quantization, sparsification and local computations. In: Advances in Neural Information Processing Systems, vol. 32 (2019)
2. Beznosikov, A., Gorbunov, E., Berard, H., Loizou, N.: Stochastic gradient descent-ascent: unified theory and new efficient methods. In: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, vol. 206, pp. 172–235. PMLR (2023)
3. Chang, C.C., Lin, C.J.: Libsvm: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(3), 1–27 (2011)
4. Deng, Y., Mahdavi, M.: Local stochastic gradient descent ascent: convergence analysis and communication efficiency. In: Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, vol. 130, pp. 1387–1395. PMLR (2021)
5. Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, vol. 27 (2014)