SwiftCMA
Released 2019
Download on GitHub

SwiftCMA is a pure-Swift implementation of Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES).
Santiago Gonzalez Ph.D. Alumni slgonzalez [at] utexas edu
Optimizing Loss Functions Through Multivariate Taylor Polynomial Parameterization Santiago Gonzalez and Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference, 2021. 2021

Improved Training Speed, Accuracy, and Data Utilization Through Loss Function Optimization Santiago Gonzalez and Risto Miikkulainen In Proceedings of the 2020 IEEE Congress on Evolutionary Computation (CEC), July 2020. 2020