My Favorite Papers of 2017

[snickmy]

http://www.nicolabortignon.com/my-favorite-4-papers-of-2017/

[yesenadam]

Could I slip in a request here for contributions to my Ask of 3 days ago, still on top page, but not many answers yet,

What are the best scholarly papers you read in 2017?

I'm hoping for some discussion on there.

https://news.ycombinator.com/item?id=15991373

[codepie]

Slightly OT, but I wanted to know if there's any group/forum where we can read and discuss papers regularly?

I know the morning paper (https://blog.acolyer.org/), but it is not so interactive, in the sense that you can't have discussions with peers and it turns into just passive reading.

[AlexCoventry → codepie]

If you're in Boston, we have a reading group for machine learning papers. We'll start up again on the 9th.

List of papers we've discussed: https://github.com/pmiller10/cambridge-ai

Mailing list: http://mailman.mit.edu/mailman/listinfo/sipb-deeplearning

[snickmy → codepie]

At Spotify, we have a reading group. I started one at SoundCloud and at Google there were multiple focused on very specific topics. If you can prove to your company the value in investing in a reading group, you can probably start one in your company too.

KTH, Stockholm's main technical university, has an open reading group too, open to everyone. Probably if you have a big enough university in your area they have something similar.

Alternatively try reddit, ie.: on r/machinelearning. That said, the value of doing this in real life, in front of a whiteboard, is worth going extra mile and find someone to team up with.

[almata → codepie]

Not exactly what you're looking for, but maybe you or someone else might be interested on this: http://fermatslibrary.com

[shalabhc → almata]

Very interesting, thanks!

Somewhat related,a general purpose annotation platform is http://hypothes.is - a great feature is that PDF annotations are location independent because they use some kind of fingerprint to identify the document.

[dilap → codepie]

Yeah, I'd be interested in this too. Something with a lot of discussion, smallish group, to create a sense of social obligation...

(So easy to be lazy w/ the infinite world of distractions available.)

[greenpizza13]

Huge, massive, credibility-undercutting typo in the slot pulling analogy: "you loose."

I'm not sure when people started making this mistake, but it's one of my more cringe-worthy ones to see.

[financequoll → greenpizza13]

You find a rather common spelling mistake (which has been fixed) “credibility-undercutting” and “cringeworthy”? It seems like you are holding blog posts that have made it to the first page of Hacker News to a ridiculously high standard.

[retrievergias]

TFX is indeed quite a massive one. Well played Google

[jacksmith21006]

My favorite is the Jeff Dean paper from NIPS in using NN for data base indexes.

[snickmy → jacksmith21006]

You are referring to this http://learningsys.org/nips17/assets/slides/dean-nips17.pdf, right?

It didn't make the cut just because is a keynote and not a paper, but nevertheless is a great engineering fit. Even more if considering that in the meanwhile Jeff is running the entire brain team, and keep pouring contributions on a regular basis: https://research.google.com/pubs/jeff.html

[stablemap → snickmy]

There is a paper for the index structure part; several authors.

https://arxiv.org/abs/1712.01208

[snickmy → stablemap]

Ah, great catch! thanks for sharing

[tommyhansen]

I wish Apple was sharing even more, and not just on Machine learning.

[arvinder]

Website broken with Firefox on Android.