Cyclical Learning Rates for Training Neural Networks — part 3/3

Cleaned-text code points [31433, 33091). Bibliography omitted here; source.md includes it.

This work has not explored the full range of applications for cyclic learning rate methods. We plan to determine if equivalent policies work for training different architectures, such as recurrent neural networks. Furthermore, we believe that a theoretical analysis would provide an improved understanding of these methods, which might lead to improvements in the algorithms.

## Appendix A Instructions for adding CLR to Caffe

Modify SGDSolver¡Dtype¿::GetLearningRate() which is in sgd_solver.cpp (near line 38):

⬇

Modify message SolverParameter which is in caffe.proto (near line 100):

⬇

## Appendix B Instructions for adding CLR to Keras

Please see https://github.com/bckenstler/CLR.

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