This library provides convenient tools for people to create their own seldonian algorithms with optimum performance. A detailed example is also included in dynamic_training.ipynb. Performance test is in ci_performance.ipynb.
gym==0.17.3numpy==1.19.1scipy==1.5.2numba == 0.51.2
- Definition of Seldonian Framework
- Definition of different Importance Sampling estimators
- Definition of the new concentration bound