• Corpus ID: 12980053

# Learning Depth-Three Neural Networks in Polynomial Time

@article{Goel2017LearningDN,
title={Learning Depth-Three Neural Networks in Polynomial Time},
author={Surbhi Goel and Adam R. Klivans},
journal={ArXiv},
year={2017},
volume={abs/1709.06010}
}
• Published 18 September 2017
• Computer Science
• ArXiv
We give a polynomial-time algorithm for learning neural networks with one hidden layer of sigmoids feeding into any smooth, monotone activation function (e.g., sigmoid or ReLU). We make no assumptions on the structure of the network, and the algorithm succeeds with respect to {\em any} distribution on the unit ball in $n$ dimensions (hidden weight vectors also have unit norm). This is the first assumption-free, provably efficient algorithm for learning neural networks with more than one hidden…
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