Machine Learning (Theory)


Fall Machine Learning Events

Many Machine Learning related events are coming up this fall.

  1. September 9, abstracts for the New York Machine Learning Symposium are due. Send a 2 page pdf, if interested, and note that we:
    1. widened submissions to be from anybody rather than students.
    2. set aside a larger fraction of time for contributed submissions.
  2. September 15, there is a machine learning meetup, where I’ll be discussing terascale learning at AOL.
  3. September 16, there is a CS&Econ day at New York Academy of Sciences. This is not ML focused, but it’s easy to imagine interest.
  4. September 23 and later NIPS workshop submissions start coming due. As usual, there are too many good ones, so I won’t be able to attend all those that interest me. I do hope some workshop makers consider ICML this coming summer, as we are increasing to a 2 day format for you. Here are a few that interest me:
    1. Big Learning is about dealing with lots of data. Abstracts are due September 30.
    2. The Bayes Bandits workshop. Abstracts are due September 23.
    3. The Personalized Medicine workshop
    4. The Learning Semantics workshop. Abstracts are due September 26.
    5. The ML Relations workshop. Abstracts are due September 30.
    6. The Hierarchical Learning workshop. Challenge submissions are due October 17, and abstracts are due October 21.
    7. The Computational Tradeoffs workshop. Abstracts are due October 17.
    8. The Model Selection workshop. Abstracts are due September 24.
  5. October 16-17 is the Singularity Summit in New York. This is for the AIists and only peripherally about ML.
  6. October 16-21 is a Predictive Analytics World in New York. As machine learning goes industrial, we see industrial-style conferences rapidly developing.
  7. October 21, there is the New York ML Symposium. In addition to what’s there, Chris Wiggins is looking into setting up a session for startups and those interested in them to get to know each other, as last year.
  8. Decembr 16-17 NIPS workshops in Granada, Spain.


Centmail comments

Tags: Economics,Problems jl@ 7:52 am

Centmail is a scheme which makes charity donations have a secondary value, as a stamp for email. When discussed on newscientist, slashdot, and others, some of the comments make the academic review process appear thoughtful :) . Some prominent fallacies are:

  1. Costing money fallacy. Some commenters appear to believe the system charges money per email. Instead, the basic idea is that users get an extra benefit from donations to a charity and participation is strictly voluntary. The solution to this fallacy is simply reading the details.
  2. Single solution fallacy. Some commenters seem to think this is proposed as a complete solution to spam, and since not everyone will opt to participate, it won’t work. But a complete solution is not at all necessary or even possible given the flag-day problem. Deployed machine learning systems for fighting spam are great at taking advantage of a partial solution. The solution to this fallacy is learning about machine learning. In the current state of affairs, informed comment about spam fighting without knowing machine learning is difficult to imagine.
  3. Broken crypto fallacy. Some commenters seem to think that stamps can be reused arbitrarily on emails. This ignores the existence of strong hashes. The solution to this fallacy is simply checking the details and possibly learning about cryptographics hashes.

Dan Reeves made a very detailed FAQ trying to address all the failure modes seen in comments, and there is a bit more discussion at messy matters.

My personal opinion is that Centmail is an interesting idea that might work, avoids the failure modes of many other ideas, hasn’t failed yet, and hence is worth trying. It’s a better approach than my earlier thoughts on economic solutions to spam.

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