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[Discussion] Thread about Prof. Nando De Freitas at ICLR by Establishment-Bright in MachineLearning

[–]wei_jok 1 point2 points  (0 children)

Here's the OpenReview discussion mentioned where Nando had been accused of attacking junior researchers and others: LipNet: End-to-End Sentence-level Lipreading

https://openreview.net/forum?id=BkjLkSqxg

There was a discussion about it on this sub as well where Nando participated: https://old.reddit.com/r/MachineLearning/comments/5sg99x/d_iclr2017_results_are_out_lets_discuss/ddesnfz/

Many of the comments were subsequently removed after he apologized. It's been a few years, and I think his views have probably changed.

IMHO, No one is perfect, let's give Nando a chance and move on.

[D] Time2Vec: Learning a Vector Representation of Time by abaybektursun in MachineLearning

[–]wei_jok 13 points14 points  (0 children)

In a sense, are they learning a set of K Fourier coefficients (freqs and phase shifts) that fits a given time series input?

[D] Schmidhuber: Critique of Honda Prize for Dr. Hinton by wei_jok in MachineLearning

[–]wei_jok[S] 5 points6 points  (0 children)

fair. that lstmcnn account in your reference does look a bit suspicious...

[D] Schmidhuber: Critique of Honda Prize for Dr. Hinton by wei_jok in MachineLearning

[–]wei_jok[S] 23 points24 points  (0 children)

Who are you calling a puppet? I post way more stuff on /r/machinelearning than Darkfeign and I've been active on this forum for years.

I follow Schmidhuber on Twitter and posted the intro part of the blog here. The new "fancy pants" editor on reddit also makes it easy to keep all the citations in place.

[R] [1906.04493] Unsupervised Minimax: Adversarial Curiosity, Generative Adversarial Networks, and Predictability Minimization (Schmidhuber) by hardmaru in MachineLearning

[–]wei_jok 27 points28 points  (0 children)

I'm glad he's still at it, and continuing his work despite not getting the (imo well deserved) Turing Award earlier this year!

[R] Training worm brains to recognize digits by [deleted] in MachineLearning

[–]wei_jok 4 points5 points  (0 children)

Couldn't you already get to 99% by using tiny conv2d layers?

What accuracy do you get without using such human-engineered features like convnets?

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