This is SCBFGS version 1.0. It has only moderately been tested. If you encounter any significant bugs, then please contact Frank E. Curtis.
SCBFGS (Self-Correcting BFGS Algorithm for Stochastic Optimization) is a prototype code for solving stochastic optimization problems. The code allows various algorithmic options, each trying to exploit the self-correcting properties of BFGS-type updating. A sample logistic regression problem is provided in order to illustrate how other problems can be formulated and solved with the code.
The code is written in Matlab and released under the MIT License.
SCBFGS is provided free of charge so that it might be useful to others. Please send e-mail to Frank E. Curtis with success stories or other feedback. If you use SCBFGS in your research, then please cite the following paper:
- Frank E. Curtis. "A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization." In Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016.