@Book{Numerical-Optimization-2006,
  author    = {Jorge Nocedal and Stephen J. Wright},
  publisher = {Springer},
  title     = {Numerical Optimization},
  year      = {2006},
  address   = {New York, NY, USA},
  edition   = {2e},
}

@article{convergence_lbfgs,
    title   = {On the limited memory BFGS method for large scale optimization},
    volume  = {45},
    DOI     = {10.1007/bf01589116},
    number  = {1–3},
    journal = {Mathematical Programming},
    author  = {Liu, Dong C. and Nocedal, Jorge},
    year    = {1989},
    month   = {8},
    pages   = {503–528}
}

@ARTICLE{BenchmarkTools,
  author    = {{Chen}, Jiahao and {Revels}, Jarrett},
  title     = "{Robust benchmarking in noisy environments}",
  journal   = {arXiv e-prints},
  keywords  = {Computer Science - Performance, 68N30, B.8.1, D.2.5},
  year      = 2016,
  month     = 8,
  eid       = {arXiv:1608.04295},
  archivePrefix = {arXiv},
  eprint    = {1608.04295},
  primaryClass = {cs.PF},
  adsurl    = {https://ui.adsabs.harvard.edu/abs/2016arXiv160804295C},
  adsnote   = {Provided by the SAO/NASA Astrophysics Data System}
}

@INPROCEEDINGS {Dogleg,
    author = {N. Ampazis and S. Spirou and S. Perantonis},
    booktitle = {Neural Networks, IEEE - INNS - ENNS International Joint Conference on},
    title = {Training Feedforward Neural Networks with the Dogleg Method and BFGS Hessian Updates},
    year = {2000},
    volume = {2},
    issn = {1098-7576},
    pages = {1138},
    abstract = {In this paper, we introduce an advanced optimization algorithm for training feedforward neural networks. The algorithm combines the BFGS Hessian update formula with a special case of trust region techniques, called the Dogleg method, as an altenative technique to line search methods. Simulations regarding classification and function approximation problems are presented which reveal a clear improvement both in convergence and success rates over standard BFGS implementations.},
    doi = {10.1109/IJCNN.2000.857827},
    url = {https://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857827},
    publisher = {IEEE Computer Society},
    address = {Los Alamitos, CA, USA},
    month = 7
}