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2011 ML symposium and the bears

The New York ML symposium was last Friday. Attendance was 268, significantly larger than last year. My impression was that the event mostly still fit the space, although it was crowded. If anyone has suggestions for next year, speak up.

The best student paper award went to Sergiu Goschin for a cool video of how his system learned to play video games (I can’t find the paper online yet). Choosing amongst the submitted talks was pretty difficult this year, as there were many similarly good ones.

By coincidence all the invited talks were (at least potentially) about faster learning algorithms. Stephen Boyd talked about ADMM. Leon Bottou spoke on single pass online learning via averaged SGD. Yoav Freund talked about parameter-free hedging. In Yoav’s case the talk was mostly about a better theoretical learning algorithm, but it has the potential to unlock an exponential computational complexity improvement via oraclization of experts algorithms… but some serious thought needs to go in this direction.

Unrelated, I found quite a bit of truth in Paul’s talking bears and Xtranormal always adds a dash of funny. My impression is that the ML job market has only become hotter since 4 years ago. Anyone who is well trained can find work, with the key limiting factor being “well trained”. In this environment, efforts to make ML more automatic and more easily applied are greatly appreciated. And yes, Yahoo! is still hiring too 🙂

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ML Symposium and ICML details

Everyone should have received notice for NY ML Symposium abstracts. Check carefully, as one was lost by our system.

The event itself is October 21, next week. Leon Bottou, Stephen Boyd, and Yoav Freund are giving the invited talks this year, and there are many spotlights on local work spread throughout the day. Chris Wiggins has setup 6(!) ML-interested startups to follow the symposium, which should be of substantial interest to the employment interested.

I also wanted to give an update on ICML 2012. Unlike last year, our deadline is coordinated with AIStat (which is due this Friday). The paper deadline for ICML has been pushed back to February 24 which should allow significant time for finishing up papers after the winter break. Other details may interest people as well:

  1. We settled on using CMT after checking out the possibilities. I wasn’t looking for this, because I’ve often found CMT clunky in terms of easy access to the right information. Nevertheless, the breadth of features and willingness to support new/better approaches to reviewing was unrivaled. We are also coordinating with Laurent, Rich, and CMT to enable their paper/reviewer recommendation system. The outcome should be a standardized interface in CMT for any recommendation system, which others can then code to if interested.
  2. Area chairs have been picked. The list isn’t sacred, so if we discover significant holes in expertise we’ll deal with it. We expect to start inviting PC members in a little while. Right now, we’re looking into invited talks. If you have any really good suggestions, they could be considered.
  3. CCC is interested in sponsoring travel costs for any climate/environment related ML papers, which seems great to us. In general, this seems like an area of growing interest.
  4. We now have a permanent server and the beginnings of the permanent website setup. Much more work needs to be done here.
  5. We haven’t settled yet on how videos will work. Last year, ICML experimented with Weyond with results here. Previously, ICML had used videolectures, which is significantly more expensive. If you have an opinion about cost/quality tradeoffs or other options, speak up.
  6. Plans for COLT have shifted slightly—COLT will start a day early, overlap with tutorials, then overlap with a coordinated first day of ICML conference papers.
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Monday announcements

Various people want to use hunch.net to announce things. I’ve generally resisted this because I feared hunch becoming a pure announcement zone while I am much more interested contentful posts and discussion personally. Nevertheless there is clearly some value and announcements are easy, so I’m planning to summarize announcements on Mondays.

  1. D. Sculley points out an interesting Semisupervised feature learning competition, with a deadline of October 17.
  2. Lihong Li points out the webscope user interaction dataset which is the first high quality exploration dataset I’m aware of that is publicly available.
  3. Seth Rogers points out CrossValidated which looks similar in conception to metaoptimize, but directly using the stackoverflow interface and with a bit more of a statistics twist.