1. Agarwal, N., Bullins, B., Hazan, E.: Second-order stochastic optimization for machine learning in linear time. J. Mach. Learn. Res. 18, 116:1–116:40 (2017)
2. Beck, A.: Introduction to Nonlinear Optimization - Theory, Algorithms, and Applications with MATLAB, MOS-SIAM Series on Optimization, vol. 19. SIAM (2014)
3. Bullins, B., Patel, K.K., Shamir, O., Srebro, N., Woodworth, B.E.: A stochastic newton algorithm for distributed convex optimization. In: Annual Conference on Neural Information Processing Systems, NeurIPS, pp. 26818–26830 (2021)
4. Byrd, R.H., Hansen, S.L., Nocedal, J., Singer, Y.: A stochastic quasi-newton method for large-scale optimization. SIAM J. Optim. 26(2), 1008–1031 (2016)
5. Chen, J., Yuan, R., Garrigos, G., Gower, R.M.: SAN: stochastic average newton algorithm for minimizing finite sums. In: International Conference on Artificial Intelligence and Statistics, AISTATS. Proceedings of Machine Learning Research, vol. 151, pp. 279–318. PMLR (2022)