Funder
Advanced Scientific Computing Research
Publisher
Springer Science and Business Media LLC
Reference33 articles.
1. Aires, N.: Algorithms to find exact inclusion probabilities for conditional Poisson sampling and Pareto $$\pi $$ps sampling designs. Methodol. Comput. Appl. Probab. 1(4), 457–469 (1999). https://doi.org/10.1023/A:1010091628740
2. Blanchet, J., Cartis, C., Menickelly, M., Scheinberg, K.: Convergence rate analysis of a stochastic trust-region method via supermartingales. INFORMS J. Optim. 1(2), 92–119 (2019). https://doi.org/10.1287/ijoo.2019.0016
3. Bollapragada, R., Menickelly, M., Nazarewicz, W., O’Neal, J., Reinhard, P.-G., Wild, S.M.: Optimization and supervised machine learning methods for fitting numerical physics models without derivatives. J. Phys. G Nucl. Part. Phys. 48(2), 024001 (2020). https://doi.org/10.1088/1361-6471/abd009
4. Bottou, L., Bousquet, O.: The tradeoffs of large scale learning. In: Advances in Neural Information Processing Systems (2007). https://papers.neurips.cc/paper/2007/hash/0d3180d672e08b4c5312dcdafdf6ef36-Abstract.html
5. Bottou, L., Curtis, F.E., Nocedal, J.: Optimization methods for large-scale machine learning. SIAM Rev. 60(2), 223–311 (2018). https://doi.org/10.1137/16m1080173