Unfortunately, I ended up sick for much of this ICML. I did manage to catch one interesting paper:
Richard Socher, Cliff Lin, Andrew Y. Ng, and Christopher D. Manning Parsing Natural Scenes and Natural Language with Recursive Neural Networks.
I invited Richard to share his list of interesting papers, so hopefully we’ll hear from him soon. In the meantime, Paul and Hal have posted some lists.
the future
Joelle and I are program chairs for ICML 2012 in Edinburgh, which I previously enjoyed visiting in 2005. This is a huge responsibility, that we hope to accomplish well. A part of this (perhaps the most fun part), is imagining how we can make ICML better. A key and critical constraint is choosing things that can be accomplished. So far we have:
- Colocation. The first thing we looked into was potential colocations. We quickly discovered that many other conferences precomitted their location. For the future, getting a colocation with ACL or SIGIR, seems to require more advanced planning. If that can be done, I believe there is substantial interest—I understand there was substantial interest in the joint symposium this year. What we did manage was achieving a colocation with COLT and there is an outside chance that a machine learning summer school will precede the main conference. The colocation with COLT is in both time and space, with COLT organized as (essentially) a separate track in a nearby building. We look forward to organizing a joint invited session or two with the COLT program chairs.
- Tutorials. We don’t have anything imaginative here, except for pushing for quality tutorials, probably through a mixture of invitations and a call. There is a small chance we’ll be able to organize a machine learning summer school as a prequel, which would be quite cool, but several things have to break right for this to occur.
- Conference. We are considering a few tinkerings with the conference format.
- Shifting a conference banquet to be during the workshops, more tightly integrating the workshops.
- Having 3 nights of posters (1 per day) rather than 2 nights. This provides more time/poster, and avoids halving talks and posters appear on different days.
- Having impromptu sessions in the evening. Two possibilities here are impromptu talks and perhaps a joint open problems session with COLT. I’ve made sure we have rooms available so others can organize other things.
- We may go for short presentations (+ a poster) for some papers, depending on how things work out schedulewise. My opinions on this are complex. ICML is traditionally multitrack with all papers having a 25 minute-ish presentation. As a mechanism for research, I believe this is superior to a single track conference of a similar size because:
- Typically some talk of potential interest can always be found by participants avoiding the boredom problem which comes up at a single track conference
- My experience is that program organizers have a limited ability to foresee which talks are of most interest, commonly creating a misallocation of attention.
On the other hand, there are clearly limits to the number of tracks that are reasonable, and I feel like ICML (especially with COLT cotimed) is near the upper limit. There are also some papers which have a limited scope of interest, for which a shorter presentation is reasonable.
- Workshops. A big change here—we want to experiment with 2 days of workshops rather than 1. There seems to be demand for it, as the number of workshops historically is about 10, enough that it’s easy to imagine people commonly interested in 2 workshops. It’s also the case that NIPS has had to start rejecting a substantial fraction of workshop submissions for space reasons. I am personally a big believer in workshops as a mechanism for further research, so I hope this works out well.
Journal integration. I tend to believe that we should be shifting to a journal format for ICML papers, as per many past discussions. After thinking about this the easiest way seems to be simply piggybacking on existing journals such as JMLR and MLJ by essentially declaring that people could submit there first, and if accepted, and not otherwise presented at a conference, present at ICML. This was considered too large a change, so it is not happening. Nevertheless, it is a possible tweak that I believe should be considered for the future. My best guess is that this would never displace the baseline conference review process, but it would help some papers that don’t naturally fit into a conference format while keeping quality high.- Reviewing. Drawing on plentiful experience with what goes wrong, I think we can create the best reviewing system for conferences. We are still debating exact details here while working through what is possible in different conference systems. Nevertheless, some basic goals are:
- Double Blind [routine now] Two identical papers with different authors should have the same chance of success. In terms of reviewing quality, I think double blind makes little difference in the short term, but the public commitment to fair reviewing makes a real difference in the long term.
- Author Feedback [routine now] Author feedback makes a difference in only a small minority of decisions, but I believe its effect is larger as (a) reviewer quality improves and (b) reviewer understanding improves. Both of these are silent improvers of quality. Somewhat less routine, we are seeking a mechanism for authors to be able to provide feedback if additional reviews are requested, as I’ve become cautious of the late-breaking highly negative review.
- Paper Editing. Geoff Gordon tweaked AIStats this year to allow authors to revise papers during feedback. I think this is helpful, because it encourages authors to fix clarity issues immediately, rather than waiting longer. This helps with some things, but it is not a panacea—authors still have to convince reviewers their paper is worthwhile, and given the way people are first impressions are lasting impressions.
- Multisource reviewing. We want all of the initial reviews to be assigned by good yet different mechanisms. In the past, I’ve observed that the source of reviewer assignments can greatly bias the decision outcome, all the way from “accept with minor revisions” to “reject” in the case of a JMLR submission that I had. Our plan at the moment is that one review will be assigned by bidding, one by a primary area chair, and one by a secondary area chair.
- No single points of failure. When Bob Williamson and I were PC members for learning theory at NIPS, we each came to a decisions given reviews and then reconciled differences. This made a difference on about 5-10% of decisions, and (I believe) improved overall quality a bit. More generally, I’ve seen instances where an area chair has an unjustifiable dislike for a paper and kills it off, which this mechanism avoids.
- Speed. In general, I believe speed and good decision making are antagonistic. Nevertheless, we believe it is important to try to do the reviewing both quickly and well. Doing things quickly implies that we can push the submission deadline back later, providing authors more time to make quality papers. Key elements of doing things well fast are: good organization (that’s all on us), light loads for everyone involved (i.e. not too many papers), crowd sourcing (i.e. most decisions made by area chairs), and some amount of asynchrony. Altogether, we believe at the moment that two weeks can be shaved from our reviewing process.
- Website. Traditionally at ICML, every new local organizer was responsible for creating a website. This doesn’t make sense anymore, because substantial work is required there, which can and should be amortized across the years so that the website can evolve to do more for the community. We plant to create a permanent website, based around some combination of icml.cc and machinelearning.org. I think this just makes sense.
- Publishing. We are thinking about strongly encouraging authors to use arxiv for final submissions. This provides a lasting backing store for ICML papers, as well as a mechanism for revisions. The reality here is that some mistakes get into even final drafts, so a way to revise for the long term is helpful. We are also planning to videotape and make available all talks, although a decision between videolectures and Weyond has not yet been made.
Implementing all the changes above is ambitious, but I believe feasible and that each is individually beneficial and to some extent individually evaluatable. I’d like to hear any thoughts you have on this. It’s also not too late if you have further suggestions of your own.
These points all sound great. #8 in particular (arXiv) was one that we had considered trying at AISTATS, but didn’t manage to do for a variety of reasons. #5 (journal integration) also sounds really interesting, and I hope someone does try it soon. Both of these have the potential to improve dissemination greatly: arXiv for rapid turnaround, and journal integration for avoiding unnecessary compression artifacts as well as wasted effort from submitting fairly similar papers to two different venues.
There is, though, a possible side effect of #5. It’s currently common that the journal version of a paper has the benefit of additional time and hindsight compared to the conference version. #5 could hurt that property. OTOH, #8 tends to go in the other direction (perpetual opportunity to revise), so perhaps it isn’t too bad overall. I’ll be curious to see how much of a problem this effect winds up being.
I like all those changes.
Another thing I really liked at AISTATS was to have 2 paper versions: a preliminary one for people to read before the conference and a post-conference camera-ready one. It might be more work for authors but if it is, it’s probably improving the paper.
Now that you are chair, will there be an error-correcting tournament for the best paper award? 🙂
I’m certainly looking into it 🙂
Why don’t we consider giving awards for best machine learning dissertation every year similar to ICAPS (http://idm-lab.org/wiki/icaps/index.php/Main/Awards) and KDD (http://www.kdd.org/awards_dissertation.php) ?
That’s an interesting idea. There are some logistical difficulties, because it involves a bunch of extra reviewing. But I’ll look into it.