Learning to learn by gradient descent by gradient descent

NeurIPS 2016 Marcin AndrychowiczMisha DenilSergio GomezMatthew W. HoffmanDavid PfauTom SchaulBrendan ShillingfordNando de Freitas

The move from hand-designed features to learned features in machine learning has been wildly successful. In spite of this, optimization algorithms are still designed by hand... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet