Toward a Turing Machine? Microsoft & Harvard Propose Neural Networks That Discover Learning Algorithms Themselves | Synced

A research team from Microsoft and Harvard University demonstrates that neural networks can discover succinct learning algorithms on their own in polynomial time and presents an architecture that combines recurrent weight-sharing between layers and convolutional weight-sharing to reduce parameter size from even trillions of nodes down to a constant.