Neural Optimizer Search with Reinforcement Learning

We present an approach to automate the process of discovering optimization methods, with a focus on deep learning architectures. We train a Recurrent Neural Network controller to generate a string in a domain specific language that describes a mathematical update equation based on a list of primitive functions, such as the gradient, running average of the gradient, etc. The controller is trained with Reinforcement Learning to maximize the performance of a model after a few epochs.

Comments

There's unfortunately not much to read here yet...

Discover the Best of Machine Learning.

Ever having issues keeping up with everything that's going on in Machine Learning? That's where we help. We're sending out a weekly digest, highlighting the Best of Machine Learning.

Join over 900 Machine Learning Engineers receiving our weekly digest.

Best of Machine LearningBest of Machine Learning

Discover the best guides, books, papers and news in Machine Learning, once per week.

Twitter