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by OriolVinyalsML on 2018-06-26 (UTC).

Welcome back, gradients! This method is orders of magnitude faster than state-of-the-art non-differentiable techniques.

DARTS: Differentiable Architecture Search by Hanxiao Liu, Karen Simonyan, and Yiming Yang.

Paper: https://t.co/gnKLXx6Pi9
Code: https://t.co/fZYIYNhLzz pic.twitter.com/pIHg3krnAE

— Oriol Vinyals (@OriolVinyalsML) June 26, 2018
research
by jeremyphoward on 2018-06-26 (UTC).

This looks quite encouraging. Still some room for improvement in the results, but a good direction for Neural Architecture Search https://t.co/fJbkOMptAr

— Jeremy Howard (@jeremyphoward) June 26, 2018
research
by PyTorch on 2018-06-26 (UTC).

"remarkable architecture search efficiency (with 4 GPUs: 2.83% error on CIFAR10 in 1 day; 56.1 perplexity on PTB in 6 hours)"
Try it now from: https://t.co/8khIix99mahttps://t.co/HFuW0II5Hl

— PyTorch (@PyTorch) June 26, 2018
researchpytorch

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