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I was just at NeurIPS (gave a spotlight talk in the session on online learning). TBH, NeurIPS gas grown too big for it's own good; this year there were 14,000 a

I was just at NeurIPS (gave a spotlight talk in the session on online learning). TBH, NeurIPS gas grown too big for it's own good; this year there were 14,000 attendees. It's so big that they had to restrict access to some of the poster sessions due to overcrowding. It's become very difficult for junior researchers to find and talk to senior people, due to the sheer size of it all; honestly, it feels like an overcrowded science fair crossed with an industry expo. I much prefer AISTATS, which I attended this year in Okinawa, Japan. Much smaller, more accessible, and with more focus on disseminating scientific ideas, as it should be.

deleted 7y ago
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softwaredoug 7y ago
Probably also too many people are focused on a solution, and not problems for specific domains. Learning more about deep learning is cool, but in practice, most problems in domains need domain expertise combined with more mundane models. This is particularly true when you need to rally domain experts help - folks able to understand logistic regression more easily than a complex deep learning model.
- MAXPOOL 7y ago
  NeurIPS should be about fundamental science not about applied science and engineering solutions for specific domains. Science vs applications would be actually a good way to divide NeurIPS into two conferences to get focus back: NeurIPS and Applied NeurIPS. One wold present science, the other tweaks, tricks and methods to solve everyday problems. Papers like "Partially Encrypted Deep Learning using Functional Encryption", "Dancing to Music", "Differentiable Cloth Simulation for Inverse Problems" would go go the engineering conference for the "most people".
  - elcomet 7y ago
    > Partially Encrypted Deep Learning using Functional Encryption I don't agree about this one. It does seem fundamental science to me.
    - b3kart 7y ago
      And here we see the problem with this particular way of splitting. Although I agree NeurIPS needs to be split up somehow.
    - nabla9 7y ago
      Encrypting deep learning is problem for practical applications that require privacy. That's applied science.
      - ses1984 7y ago
        How do you suppose you're going to provide theoretical assurance of privacy and correctness without science?
        nabla9 7y ago
        Maybe I'm wrong but I see this as applied vs fundamental, not "without science" issue.
      - elcomet 7y ago
        Well machine learning is applied science. But inside there are theoretical work (like encrypted machine learning or optimization theory) and practical work (like text2speech, or other tasks)
      - Vervious 7y ago
        Disagree. Theory is always interested in building better, simpler protocols, asking questions about lower bounds and possibility. See almost all of fundamental crypto research.
  - softwaredoug 7y ago
    Right I agree. I mean to try to explain why so many go to this conference, not to criticize the conference itself.
fieldmeasure 7y ago
I completely agree. I have been on ICCV this year (only 7500 participants) and found it really difficult to find people who I would like to talk to (e.g. because they had a nice presentation). The number of submissions has doubled since the last time (two years ago) [0]. It is just a constant overflow of information and the conference (including workshops, which were pretty good) lasted seven days. I think these ML/DL conferences need to be split up and specialize more to manage the interest. [0] https://github.com/hoya012/ICCV-2019-Paper-Statistics https://github.com/hoya012/ICCV-2019-Paper-Statistics
joshvm 7y ago
I had a workshop spotlight. Those sessions were generally a lot calmer. A big problem was cramming hundreds of posters in one large space, with a relatively poor search experience (posters were kind of arbitrarily organised with some categories only having three or four entries). If they'd split them over both exhibition centres (or multiple rooms/floors), it might have calmed the crowds. Also since it was hard to know exactly where to look, there was a lot of wandering around. There's also the heavy corporate side where people spent the evenings going to not-so-secret invite-only parties (lots of FOMO going on). Lots of jobs going, but ridiculous amount of competition now. Despite that it was pretty friendly, and I had good results emailing people I wanted to chat to, and going to the socials. Really the field needs to start publishing in journals again, and not obsessing over one or two mega-conferences each year. In other domains, there are huge congress events, but they're much more informal (eg EGU, 17k people).
chillee 7y ago
Perhaps I'll provide a contrary view. I was also at Neurips, and I'm also a junior researcher. Yes, it was massive, and the poster sessions were crowded. However, I was still able to talk to everybody I wanted to talk to - often for long periods of time. Many of them I sent emails to, and I was able to talk with everybody I wanted to (except 1), many who would be considered senior researchers. Disseminating scientific ideas is really only one part of what a conference is meant to do. The other part is networking, and that was extremely valuable for me.

deleted 7y ago

[deleted]

softwaredoug 7y ago

Probably also too many people are focused on a solution, and not problems for specific domains. Learning more about deep learning is cool, but in practice, most problems in domains need domain expertise combined with more mundane models. This is particularly true when you need to rally domain experts help - folks able to understand logistic regression more easily than a complex deep learning model.

MAXPOOL 7y ago
NeurIPS should be about fundamental science not about applied science and engineering solutions for specific domains. Science vs applications would be actually a good way to divide NeurIPS into two conferences to get focus back: NeurIPS and Applied NeurIPS. One wold present science, the other tweaks, tricks and methods to solve everyday problems. Papers like "Partially Encrypted Deep Learning using Functional Encryption", "Dancing to Music", "Differentiable Cloth Simulation for Inverse Problems" would go go the engineering conference for the "most people".
- elcomet 7y ago
  > Partially Encrypted Deep Learning using Functional Encryption I don't agree about this one. It does seem fundamental science to me.
  - b3kart 7y ago
    And here we see the problem with this particular way of splitting. Although I agree NeurIPS needs to be split up somehow.
  - nabla9 7y ago
    Encrypting deep learning is problem for practical applications that require privacy. That's applied science.
    - ses1984 7y ago
      How do you suppose you're going to provide theoretical assurance of privacy and correctness without science?
      - nabla9 7y ago
        Maybe I'm wrong but I see this as applied vs fundamental, not "without science" issue.
    - elcomet 7y ago
      Well machine learning is applied science. But inside there are theoretical work (like encrypted machine learning or optimization theory) and practical work (like text2speech, or other tasks)
    - Vervious 7y ago
      Disagree. Theory is always interested in building better, simpler protocols, asking questions about lower bounds and possibility. See almost all of fundamental crypto research.
- softwaredoug 7y ago
  Right I agree. I mean to try to explain why so many go to this conference, not to criticize the conference itself.

fieldmeasure 7y ago

I completely agree. I have been on ICCV this year (only 7500 participants) and found it really difficult to find people who I would like to talk to (e.g. because they had a nice presentation). The number of submissions has doubled since the last time (two years ago) [0]. It is just a constant overflow of information and the conference (including workshops, which were pretty good) lasted seven days. I think these ML/DL conferences need to be split up and specialize more to manage the interest. [0] https://github.com/hoya012/ICCV-2019-Paper-Statistics https://github.com/hoya012/ICCV-2019-Paper-Statistics

joshvm 7y ago

I had a workshop spotlight. Those sessions were generally a lot calmer. A big problem was cramming hundreds of posters in one large space, with a relatively poor search experience (posters were kind of arbitrarily organised with some categories only having three or four entries). If they'd split them over both exhibition centres (or multiple rooms/floors), it might have calmed the crowds. Also since it was hard to know exactly where to look, there was a lot of wandering around. There's also the heavy corporate side where people spent the evenings going to not-so-secret invite-only parties (lots of FOMO going on). Lots of jobs going, but ridiculous amount of competition now. Despite that it was pretty friendly, and I had good results emailing people I wanted to chat to, and going to the socials. Really the field needs to start publishing in journals again, and not obsessing over one or two mega-conferences each year. In other domains, there are huge congress events, but they're much more informal (eg EGU, 17k people).

chillee 7y ago

Perhaps I'll provide a contrary view. I was also at Neurips, and I'm also a junior researcher. Yes, it was massive, and the poster sessions were crowded. However, I was still able to talk to everybody I wanted to talk to - often for long periods of time. Many of them I sent emails to, and I was able to talk with everybody I wanted to (except 1), many who would be considered senior researchers. Disseminating scientific ideas is really only one part of what a conference is meant to do. The other part is networking, and that was extremely valuable for me.