Learned Optimizers that Scale and Generalize
ICML, 2017.
EI
Abstract:
Learning to learn has emerged as an important direction for achieving artificial intelligence. Two of the primary barriers to its adoption are an inability to scale to larger problems and a limited ability to generalize to new tasks. We introduce a learned gradient descent optimizer that generalizes well to new tasks, and which has signif...More
Code:
Data:
Tags
Comments