NN training goes through two distinct phases: (1) reducing classification error through drift (2) optimally compressing mutual information of hidden layers through diffusion https://arxiv.org/abs/1703.00810 pic.twitter.com/He7dNY3NSv
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If I’m reading right that they’ve spun a general theory of DL based on runs discriminating inside/outside of a hypersphere, everyone should be laughing at them.
I’m not sure what is in the supplementary material (can’t easily find) but based on this bit, sounds like all studies were done with trivial synthetic data. If so this is a nice intro class project, not a publishable result, much less a breakthrough.pic.twitter.com/msWSGp9NM8
I might be missing something, and they also might happen to have found something real even though there’s no meaningful evidence for it here.
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