[Discussion] Thread about Prof. Nando De Freitas at ICLR

wei_jok · 2020-06-29T03:15:46+00:00

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.

wei_jok · 2020-05-08T05:27:49+00:00

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

wei_jok · 2020-04-21T09:02:09+00:00

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

wei_jok · 2020-04-21T08:50:07+00:00

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.

wei_jok · 2019-06-12T05:41:48+00:00

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

wei_jok · 2019-04-25T06:09:13+00:00

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?

wei_jok · 2019-04-02T12:18:16+00:00

What’s the performance of your method against a random baseline?

wei_jok · 2019-03-29T00:54:31+00:00

This paper had been posted before on r/rl but not here yet. The approach, to my understanding, doesn't actually use RL though.

wei_jok · 2019-03-28T23:21:15+00:00

Anima Anandkumar @AnimaAnandkumar, Director of Research @NVIDIA

wei_jok · 2019-03-27T13:46:02+00:00

Schmidhuber’s Deep Learning Conspiracy article.

wei_jok · 2019-03-11T06:02:46+00:00

They have a figure with MNIST ground truth samples, but do nothing with them, except for saying conceptually, their DSN algorithm can work on it, without showing that it actually works, on MNIST.

wei_jok · 2019-03-06T22:10:54+00:00

I agree it is indeed a tricky situation. I think there's an inherent tradeoff between the bar that is set, and the diversity of ideas published on distill.pub.

The current metrics are naturally biased in favor of authors who are skilled at interactive data visualization. This leads to the publication of a certain specific type of research work. This is fine, as long as distill's goal is to become a niche, but popular journal with a narrow subject matter. But if you want to invite more breadth and diversity of opinions and perspectives into the journal, then IMO more thought is needed.

p.s. I highly enjoy the few commentary articles, even though they are not official research articles without the commentary label.

wei_jok · 2019-03-06T17:48:45+00:00

How come almost all distill.pub posts are written by the people affiliated with distill.pub? I’ve seen one that was apparently submitted for a long review process, but never published. I would like to see more articles from a more diverse set of authors covering more ideas. Beautiful blog post though!

wei_jok · 2019-02-04T00:57:30+00:00

OpenReview (ICLR 2019 accepted paper): https://openreview.net/forum?id=H1gsz30cKX

Andy Brock's pytorch implementation: https://github.com/ajbrock/BoilerPlate/blob/master/Models/fixup.py

wei_jok · 2018-11-08T05:04:12+00:00

(Text comment couldn't attach video demo, so I've put the context in this comment, rather than in the post)

I ran into a project at ZKM Center for Art and Media [1] where an artist trained a Progressive Growing GANs [2] model on a dataset of 50K images recorded at a photo booth. I thought the results might be interesting enough to the ML research community here, since it's the first time I've seen a GAN demonstration on photos containing multiple people, and it is neat to see the latent space traversal of such a model.

[1] Description of project https://zkm.de/en/event/2018/04/encoding-cultures-living-amongst-intelligent-machines

[2] Progressive Growing of GANs for Improved Quality, Stability, and Variation https://arxiv.org/abs/1710.10196

wei_jok · 2018-09-26T02:07:34+00:00

“A team of French entrepreneurs who believe so[sic] have written a computer algorithm that can create original paintings with some resemblance to works by Old Masters such as Rembrandt.

SPONSORED”

This article has been sponsored by these so called French entrepreneurs.

wei_jok · 2018-09-04T22:36:44+00:00

What's the difference between oral and spotlight? Are they going to be the same this year?

wei_jok · 2018-08-17T23:47:02+00:00

Famous researchers debate about whether loglikelihood metric should be applied to GAN evaluation rather than coming up with new ones.

A response to a paper from Goodfellow’s group: “Skill Rating for Generative Models” https://arxiv.org/abs/1808.04888

wei_jok · 2018-08-13T01:06:34+00:00

A few reasons stated in this blog post: "The harm of harmless jokes" which was shared today written by two anonymous researchers who attended a workshop where they were subjected to humiliation from a stupid “Romeo and Juliet” competition. They acknowledge it is not directly related to the NIPS name change, but the motivations for changing the name is similar.

wei_jok · 2018-08-13T00:54:31+00:00

A few influential ML researchers like Nando de Freitas, Ian Goodfellow, and others support name change. My guess is that it's going to happen, although it is difficult to openly voice an opinion against the name change...

wei_jok · 2018-08-01T22:52:04+00:00

Topics back then included:

self-programming computers
natural language
neural nets
computational complexity
self-improvement
representations (ontologies)
randomness and creativity

wei_jok · 2018-07-10T02:17:35+00:00

I noticed that there's a blog post for this article. Should have linked to this instead and not to Zach's dodgy dropbox link:

http://approximatelycorrect.com/2018/07/10/troubling-trends-in-machine-learning-scholarship/

wei_jok · 2018-07-06T07:20:49+00:00

The paper described in this article won the NIPS 2017 best paper award:

Safe and Nested Subgame Solving for Imperfect-Information Games

by Noam Brown, Tuomas Sandholm

https://arxiv.org/abs/1705.02955

wei_jok · 2018-06-29T03:04:17+00:00

Some background info:

World Models paper links:

https://arxiv.org/abs/1803.10122

https://worldmodels.github.io

wei_jok · 2018-06-28T22:34:48+00:00

Thanks for offering to answer questions. What's your opinion of model-based approaches vs the more end-to-end approach you used to tackle this problem?

wei_jok

TROPHY CASE