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Welcome to the libcmaes documentation

objective function, parameters, hyper-parameters.

1. Building and installing libcmaes
2. Quick start
3. Library structures and API
4. Using libcmaes
5. Optimizing a function
6. Visualizing optimization results and convergence
7. Defining and using bounds on parameters
8. Using parameter space transforms known as genotype/phenotype transforms
9. Using a custom progress function
10. Using a user-defined gradient function
11. Defining a custom algorithm based on libcmaes primitives
12. Applications
13. using CMA-ES in CERN's ROOT
14. experiments with CMA-ES and neural networks