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Distill: a modern machine learning journal

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Re: Distill: a modern machine learning journal

#31

Post by auvrw »

curuinor wrote: post #4
colah3 wrote: post #2

Various announcements: Google Research: https://research.googleblog.com/2017/03/distill-supporting-c... DeepMind: https://deepmind.com/blog/distill-communicating-science-mach... OpenAI: https://openai.com/blog/Distill/ YC Research: http://blog.ycombinator.com/distill-an-interactive-visual-jo... Chris Olah: http://colah.github.io/posts/2017-03-Distill/

As I said in Rob's thingy, I hope you get the tenure committees and job committees, because they don't have to respect it but they're the ones you have to get to respect

in my (incredibly limited) experience, Impact Factor is also a consideration

https://en.wikipedia.org/wiki/Impact_factor

Re: Distill: a modern machine learning journal

#32

Post by findjashua »

j2kun wrote: post #18

I sure hope this catches on, but we should all be aware of the hurdles: - Little incentive for researchers to do this beyond their own good will. - Most ML researchers are bad writers, and it's unlikely that the editing team will do the work needed (which is often a larger reorganization of a paper and ideas) to improve clarity. - Producing great writing and clear, interactive figures, and managing an ongoing github…

up next: a neural net that reorganizes research papers to improve clarity

Re: Distill: a modern machine learning journal

#33

Post by auvrw »

colah3 wrote: post #13
Old_Thrashbarg wrote: post #12

I don't see it written explicitly; can anyone confirm that this journal is fully open-access?

Yes. Everything is published under Creative Commons Attribution. (One of the members of our steering committee, Michael Nielsen, has a significant history advocating for open science. I think there's about a snowball's chance in hell he'd be involved if we weren't. :P )

> Everything is published under Creative Commons Attribution.

this is tres bien.

same for data sets?

Re: Distill: a modern machine learning journal

#35

Post by arjunnarayan »

colah3 wrote: post #7
curuinor wrote: post #4

Earlier quoted context omitted.

As I said in Rob's thingy, I hope you get the tenure committees and job committees, because they don't have to respect it but they're the ones you have to get to respect

All we can do is work hard to build academic support: * In the last three weeks, we've had 80 outreach conversations with various stakeholders for Distill. The majority of these have been academic researchers. The response has been extremely positive. * A number of ML faculty at Stanford / Berkeley / Toronto / Montreal are very excited and supportive of Distill. * Distill's steering committee consists of recognized l…

Can you share a "behind the scenes" of what it took to get Distill off the ground? You hint at dotting your "i"s and crossing your "t"s, but an explicit manual would be useful. Other communities than just machine learning could benefit from something like this, and if Distill succeeds in being taken seriously by your research community, it would help to have a playbook in which to replicate that success in other research communities as well.

Re: Distill: a modern machine learning journal

#36

Post by mlinksva »

colah3 wrote: post #13
Old_Thrashbarg wrote: post #12

I don't see it written explicitly; can anyone confirm that this journal is fully open-access?

Yes. Everything is published under Creative Commons Attribution. (One of the members of our steering committee, Michael Nielsen, has a significant history advocating for open science. I think there's about a snowball's chance in hell he'd be involved if we weren't. :P )

It's not super clear what if any license is offered for code and data, eg from http://distill.pub/2016/misread-tsne/

> Diagrams and text are licensed under Creative Commons Attribution CC-BY 2.0, unless noted otherwise, with the source available on GitHub. The figures that have been reused from other sources don’t fall under this license and can be recognized by a note in their caption: “Figure from …”.

Ideally code and data would be unambiguously public domain (CC0-1.0) or under appropriate open source and open data licenses.

Re: Distill: a modern machine learning journal

#37

Post by rspeer »

auvrw wrote: post #33
colah3 wrote: post #13

Earlier quoted context omitted.

Yes. Everything is published under Creative Commons Attribution. (One of the members of our steering committee, Michael Nielsen, has a significant history advocating for open science. I think there's about a snowball's chance in hell he'd be involved if we weren't. :P )

> Everything is published under Creative Commons Attribution. this is tres bien. same for data sets?

That would preclude most research data.

If you use Wikipedia as an input, for example, your data is CC-By-SA, not CC-By.

Re: Distill: a modern machine learning journal

#38

Post by pininja »

colah3 wrote: post #22
j2kun wrote: post #18

I sure hope this catches on, but we should all be aware of the hurdles: - Little incentive for researchers to do this beyond their own good will. - Most ML researchers are bad writers, and it's unlikely that the editing team will do the work needed (which is often a larger reorganization of a paper and ideas) to improve clarity. - Producing great writing and clear, interactive figures, and managing an ongoing github…

You're absolutely right that this is a lot of work, and not many ML researchers have all the skills needed for it. In the short term, Distill's editorial assistance will help authors produce outstanding papers, although they need to be willing to work as well. In the longer-term, I'd like to explore match making between data visualization people who would like to get into machine learning and machine learning researc…

I fall into the longer-term category as a front end data visualization person who would like to learn more ML. Please reach out to me if you're looking for JS volunteer to help with code review, visualization polish, or implementing new visualizations.

Re: Distill: a modern machine learning journal

#39

Post by fnl »

How does this provide IF ratings? Probably irrelevant for industry, but publishing in academia is all about IF, no matter how bad and corrupt one might think it is.

And what about long-term stability/presence. Most top journals and their publishing houses (NPG, Elsevier, Springer) are likely to hang around for another decade (or two...), while I don't feel so sure about that for a product like GitHub. Maybe Distill is/will be officially backed (financially) by the industry names supporting it?

That being said, I'd love seeing this succeed, but there seems much to be done to get this really "off the ground" beyond being a (much?!) nicer GitXiv.

Re: Distill: a modern machine learning journal

#40

Post by [deleted] »

j2kun wrote: post #18

I sure hope this catches on, but we should all be aware of the hurdles: - Little incentive for researchers to do this beyond their own good will. - Most ML researchers are bad writers, and it's unlikely that the editing team will do the work needed (which is often a larger reorganization of a paper and ideas) to improve clarity. - Producing great writing and clear, interactive figures, and managing an ongoing github…

[deleted]
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