hunch_net hunch_net-2012 hunch_net-2012-460 knowledge-graph by maker-knowledge-mining
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Introduction: has died . He lived a full life. I know him personally as a founder of the Center for Computational Learning Systems and the New York Machine Learning Symposium , both of which have sheltered and promoted the advancement of machine learning. I expect much of the New York area machine learning community will miss him, as well as many others around the world.
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same-blog 1 0.99999988 460 hunch net-2012-03-24-David Waltz
Introduction: has died . He lived a full life. I know him personally as a founder of the Center for Computational Learning Systems and the New York Machine Learning Symposium , both of which have sheltered and promoted the advancement of machine learning. I expect much of the New York area machine learning community will miss him, as well as many others around the world.
2 0.20222008 316 hunch net-2008-09-04-Fall ML Conferences
Introduction: If you are in the New York area and interested in machine learning, consider submitting a 2 page abstract to the ML symposium by tomorrow (Sept 5th) midnight. It’s a fun one day affair on October 10 in an awesome location overlooking the world trade center site. A bit further off (but a real conference) is the AI and Stats deadline on November 5, to be held in Florida April 16-19.
3 0.15908052 489 hunch net-2013-09-20-No NY ML Symposium in 2013, and some good news
Introduction: There will be no New York ML Symposium this year. The core issue is that NYAS is disorganized by people leaving, pushing back the date, with the current candidate a spring symposium on March 28. Gunnar and I were outvoted here—we were gung ho on organizing a fall symposium, but the rest of the committee wants to wait. In some good news, most of the ICML 2012 videos have been restored from a deep backup.
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Introduction: On Sept 21, there is another machine learning meetup where I’ll be speaking. Although the topic is contextual bandits, I think of it as “the future of machine learning”. In particular, it’s all about how to learn in an interactive environment, such as for ad display, trading, news recommendation, etc… On Sept 24, abstracts for the New York Machine Learning Symposium are due. This is the largest Machine Learning event in the area, so it’s a great way to have a conversation with other people. On Oct 22, the NY ML Symposium actually happens. This year, we are expanding the spotlights, and trying to have more time for posters. In addition, we have a strong set of invited speakers: David Blei , Sanjoy Dasgupta , Tommi Jaakkola , and Yann LeCun . After the meeting, a late hackNY related event is planned where students and startups can meet. I’d also like to point out the related CS/Econ symposium as I have interests there as well.
5 0.13627987 494 hunch net-2014-03-11-The New York ML Symposium, take 2
Introduction: The 20 13 14 is New York Machine Learning Symposium is finally happening on March 28th at the New York Academy of Science . Every invited speaker interests me personally. They are: Rayid Ghani (Chief Scientist at Obama 2012) Brian Kingsbury (Speech Recognition @ IBM) Jorge Nocedal (who did LBFGS) We’ve been somewhat disorganized in advertising this. As a consequence, anyone who has not submitted an abstract but would like to do so may send one directly to me (jl@hunch.net title NYASMLS) by Friday March 14. I will forward them to the rest of the committee for consideration.
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Introduction: has died . He lived a full life. I know him personally as a founder of the Center for Computational Learning Systems and the New York Machine Learning Symposium , both of which have sheltered and promoted the advancement of machine learning. I expect much of the New York area machine learning community will miss him, as well as many others around the world.
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Introduction: On Sept 21, there is another machine learning meetup where I’ll be speaking. Although the topic is contextual bandits, I think of it as “the future of machine learning”. In particular, it’s all about how to learn in an interactive environment, such as for ad display, trading, news recommendation, etc… On Sept 24, abstracts for the New York Machine Learning Symposium are due. This is the largest Machine Learning event in the area, so it’s a great way to have a conversation with other people. On Oct 22, the NY ML Symposium actually happens. This year, we are expanding the spotlights, and trying to have more time for posters. In addition, we have a strong set of invited speakers: David Blei , Sanjoy Dasgupta , Tommi Jaakkola , and Yann LeCun . After the meeting, a late hackNY related event is planned where students and startups can meet. I’d also like to point out the related CS/Econ symposium as I have interests there as well.
3 0.76959503 474 hunch net-2012-10-18-7th Annual Machine Learning Symposium
Introduction: A reminder that the New York Academy of Sciences will be hosting the 7th Annual Machine Learning Symposium tomorrow from 9:30am. The main program will feature invited talks from Peter Bartlett , William Freeman , and Vladimir Vapnik , along with numerous spotlight talks and a poster session. Following the main program, hackNY and Microsoft Research are sponsoring a networking hour with talks from machine learning practitioners at NYC startups (specifically bit.ly , Buzzfeed , Chartbeat , and Sense Networks , Visual Revenue ). This should be of great interest to everyone considering working in machine learning.
4 0.76844019 494 hunch net-2014-03-11-The New York ML Symposium, take 2
Introduction: The 20 13 14 is New York Machine Learning Symposium is finally happening on March 28th at the New York Academy of Science . Every invited speaker interests me personally. They are: Rayid Ghani (Chief Scientist at Obama 2012) Brian Kingsbury (Speech Recognition @ IBM) Jorge Nocedal (who did LBFGS) We’ve been somewhat disorganized in advertising this. As a consequence, anyone who has not submitted an abstract but would like to do so may send one directly to me (jl@hunch.net title NYASMLS) by Friday March 14. I will forward them to the rest of the committee for consideration.
5 0.7591396 489 hunch net-2013-09-20-No NY ML Symposium in 2013, and some good news
Introduction: There will be no New York ML Symposium this year. The core issue is that NYAS is disorganized by people leaving, pushing back the date, with the current candidate a spring symposium on March 28. Gunnar and I were outvoted here—we were gung ho on organizing a fall symposium, but the rest of the committee wants to wait. In some good news, most of the ICML 2012 videos have been restored from a deep backup.
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Introduction: When presenting part of the Reinforcement Learning theory tutorial at ICML 2006 , I was forcibly reminded of this. There are several difficulties. When creating the presentation, the correct level of detail is tricky. With too much detail, the proof takes too much time and people may be lost to boredom. With too little detail, the steps of the proof involve too-great a jump. This is very difficult to judge. What may be an easy step in the careful thought of a quiet room is not so easy when you are occupied by the process of presentation. What may be easy after having gone over this (and other) proofs is not so easy to follow in the first pass by a viewer. These problems seem only correctable by process of repeated test-and-revise. When presenting the proof, simply speaking with sufficient precision is substantially harder than in normal conversation (where precision is not so critical). Practice can help here. When presenting the proof, going at the right p
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Introduction: The consensus of several discussions at ICML is that the number of jobs for people knowing machine learning well substantially exceeds supply. This is my experience as well. Demand comes from many places, but I’ve seen particularly strong demand from trading companies and internet startups. Like all interest bursts, this one will probably pass because of economic recession or other distractions. Nevertheless, the general outlook for machine learning in business seems to be good. Machine learning is all about optimization when there is uncertainty and lots of data. The quantity of data available is growing quickly as computer-run processes and sensors become more common, and the quality of the data is dropping since there is little editorial control in it’s collection. Machine Learning is a difficult subject to master (*), so those who do should remain in demand over the long term. (*) In fact, it would be reasonable to claim that no one has mastered it—there are just some peo
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Introduction: has died . He lived a full life. I know him personally as a founder of the Center for Computational Learning Systems and the New York Machine Learning Symposium , both of which have sheltered and promoted the advancement of machine learning. I expect much of the New York area machine learning community will miss him, as well as many others around the world.
4 0.76255369 307 hunch net-2008-07-04-More Presentation Preparation
Introduction: We’ve discussed presentation preparation before , but I have one more thing to add: transitioning . For a research presentation, it is substantially helpful for the audience if transitions are clear. A common outline for a research presentation in machine leanring is: The problem . Presentations which don’t describe the problem almost immediately lose people, because the context is missing to understand the detail. Prior relevant work . In many cases, a paper builds on some previous bit of work which must be understood in order to understand what the paper does. A common failure mode seems to be spending too much time on prior work. Discuss just the relevant aspects of prior work in the language of your work. Sometimes this is missing when unneeded. What we did . For theory papers in particular, it is often not possible to really cover the details. Prioritizing what you present can be very important. How it worked . Many papers in Machine Learning have some sor
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