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ICML registration is live

Here. I would recommend registering early because there is a difficult to estimate(*) chance you will not be able to register later.

The program is shaping up and should be of interest. The 9 Tutorials(**), 4 Invited Speakers, and 23 Workshops are all chosen, with paper decisions due out in a couple weeks.

Early Full (after May 7)
Student 510 640
Regular 840 1050

These numbers are as aggressively low as the local chairs and I can sleep with at night. The prices are higher than I’d like (New York is expensive), but a bit lower than last year, particularly for students(***).

(*) Relevant facts:

  1. ICML 2016: submissions up 30% to 1300.
  2. NIPS 2015 in Montreal: 3900 registrations (way up from last year).
  3. NIPS 2016 is in Barcelona.
  4. ICML 2015 in Lille: 1670 registrations.
  5. KDD 2014 in NYC: closed@3000 registrations 1 week before the conference.

I tried to figure out how to setup a prediction market to estimate what will happen this year, but didn’t find an easy-enough way to do that.

(**) I kind of wish we could make up the titles. How about: “Go is Too Easy” and “My Neural Network is Deeper than Yours”?

(***) Sponsors are very generous and are mostly giving to defray student costs. Approximately every dollar of the difference between Regular and Student registration is due to company donations. For students, also note that there will be some scholarship opportunities to defray costs coming out soon.

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New York Machine Learning Deadlines

There’s a number of different Machine Learning related paper deadlines that may interest.

January 29 (abstract) for March 4 New York ML Symposium Register early because NYAS can only fit 300.
January 27 (abstract)/February 2 (paper) for July 9-15 IJCAI The biggest AI conference
February 5(paper) for June 19-24 ICML Nina and Kilian have 850 well-vetted reviewers. Marek and Peder have increased space to allow 3K people.
February 12(paper) for June 23-26 COLT Vitaly and Sasha are program chairs.
February 12(proposal) for June 23-24 ICML workshops Fei and Ruslan are the workshop chairs. I really like workshops.
February 19(proposal) for June 19 ICML tutorials Bernhard and Alina have invited a few tutorials already but are saving space for good proposals as well.
March 1(paper) for June 25-29 UAI Jersey City isn’t quite New York, but it’s close enough 🙂
May ~2 for June 23-24 ICML workshops Varies with the workshop.
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CNTK and Vowpal Wabbit tutorials at NIPS

Both CNTK and Vowpal Wabbit have pirate tutorials at NIPS. The CNTK tutorial is 1 hour during the lunch break of the Optimization workshop while the VW tutorial is 1 hour during the lunch break of the Extreme Multiclass workshop. Consider dropping by either if interested.

CNTK is a deep learning system started by the speech people who started the deep learning craze and grown into a more general platform-independent deep learning system. It has various useful features, the most interesting of which is perhaps efficient scalable training. Using GPUs with allreduce and one-bit sgd it achieves both high efficiency and scalability over many more GPUs than could ever fit into a single machine. This capability is unique amongst all open deep learning codebases so everything else looks nerfed in comparison. CNTK was released in April so this is the first chance for many people to learn about it. See here for more details.

The Vowpal Wabbit tutorial just focuses on what is new this year.

  1. The learning to search framework has greatly matured and is now easily used to solve ad-hoc joint(structured) prediction problems. The ICML tutorial covers algorithms/analysis so this is about using the system.
  2. VW has also become the modeling element of a larger system (called the decision service) which gathers data and uses it as per Contextual Bandit learning. This is now generally usable, and is the first general purpose system of this sort.
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ICML 2016 in NYC and KDD Cup 2016

ICML 2016 is in New York City. I expect it to be the largest ICML by far given the destination—New York is the place which is perhaps easiest to reach from anywhere in the world and it has the largest machine learning meetup anywhere in the world.

I am the general chair this year, which is light in work but heavy in responsibilities. Some things I worry about:

  1. How many people will actually come? Numbers are difficult to guess with the field growing and the conference changing locations. I believe we need capacity for at least 3000 people based on everything I know.
  2. New York is expensive. What can be done about it? One thought is that we should actively setup a roommate finding system so the costs of hotels can be shared. Up to 3 people can share a hotel room for the conference hotel (yes, each with their own bed), and that makes the price much more reasonable. I’m also hoping donations will substantially defray the cost. If others have creative ideas, I’m definitely interested.

Markus Weimer also points out the 2016 KDD Cup which has a submission deadline of December 6. KDD Cup datasets have become common reference for many machine learning papers, so this is a good way to get your problem solved well by many people.