643 citations · 1.2k across the 13 of their papers we have counts for
3 papers · 1 filter
Population Based Training of Neural Networks
Max Jaderberg, Valentin Dalibard, Simon Osindero +9
Neural networks dominate the modern machine learning landscape, but their training and success still suffer from sensitivity to empirical choices of hyperparameters such as model a…
Hierarchical Representations for Efficient Architecture Search
Hanxiao Liu, Karen Simonyan, Oriol Vinyals +2
We explore efficient neural architecture search methods and show that a simple yet powerful evolutionary algorithm can discover new architectures with excellent performance. Our ap…
PathNet: Evolution Channels Gradient Descent in Super Neural Networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell +5
For artificial general intelligence (AGI) it would be efficient if multiple users trained the same giant neural network, permitting parameter reuse, without catastrophic forgetting…