Rémi,
Nvidia launched the K20 GPU in late 2012. Since then, GPUs and their
convolution algorithms have improved considerably, while CPU performance
has been relatively stagnant. I would expect about a 10x improvement with
2016 hardware.
When it comes to training, it's the difference between runni
Hi Brian,
Thanks for sharing your genuinely interesting result. One question though:
why would you train on a non-"zero" program? Do you think your program as a
result of your rules would perform better than zero, or is it imitating the
best known algorithm inconvenient for your purposes?
Best,
-
Hi Simon,
Thanks for sharing. In my opinion, apart from discretizing the search
space, the N-Tuple system takes a very intuitive approach to
hyper-parameter optimization. The github repo readme notes you're working
on an extended version to handle continuous parameters, what's your general
approac
Concur w/Brian. While the authors present genuine contributions,
meta-learning doesn't apply well to zero-sized architectures.
I didn't get a lot from the article, the arxiv link for the work done is
https://arxiv.org/abs/1812.00332
Best,
-Chaz
On Sun, Mar 24, 2019 at 4:17 PM Brian Lee
wrote:
