1. Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moore, S., Murray, D.G., Steiner, B., Tucker, P.A., Vasudevan, V., Warden, P., Wicke, M., Yu, Y., Zheng, X.: Tensorflow: A system for large-scale machine learning. In: Keeton, K., Roscoe , T. (eds.) 12th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2016, Savannah, GA, USA, November 2-4, 2016, pp. 265–283. USENIX Association. https://www.usenix.org/conference/osdi16/technical-sessions/presentation/abadi (2016)
2. Kairouz, P., et al.: Advances and open problems in federated learning. https://doi.org/10.1561/2200000083, vol. 14, pp 1–210 (2021)
3. Beck, A., Teboulle, M.: Smoothing and first order methods: A unified framework. SIAM J. Optim. 22(2), 557–580 (2012). https://doi.org/10.1137/100818327
4. Ben-Tal, A., Ghaoui, L. E., Nemirovski, A.: Robust Optimization, Princeton Series in Applied Mathematics, vol. 28. Princeton University Press, Princeton (2009). https://doi.org/10.1515/9781400831050
5. Ben-Tal, A., Teboulle, M.: Expected utility, penalty functions, and duality in stochastic nonlinear programming. Manage. Sci. 32, 1445–1466 (1986). https://doi.org/10.1287/mnsc.32.11.1445