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SwiftCMA
Released 2019
Download on GitHub
SwiftCMA is a pure-Swift implementation of Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES).
People
Santiago Gonzalez
Ph.D. Alumni
slgonzalez [at] utexas edu
Publications
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
Areas of Interest
Evolutionary Computation