Learned Optimizers that Scale and Generalize

ICML, 2017.

Cited by: 104|Bibtex|Views72|Links
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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

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