hunch_net hunch_net-2009 hunch_net-2009-356 knowledge-graph by maker-knowledge-mining
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Introduction: Mark Reid has setup a discussion site for ICML papers again this year and Monica Dinculescu has linked it in from the ICML site. Last year’s attempt appears to have been an acceptable but not wild success as a little bit of fruitful discussion occurred. I’m hoping this year will be a bit more of a success—please don’t be shy I’d like to also point out that ICML ‘s early registration deadline has a few hours left, while UAI ‘s and COLT ‘s are in a week.
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1 Mark Reid has setup a discussion site for ICML papers again this year and Monica Dinculescu has linked it in from the ICML site. [sent-1, score-1.069]
2 Last year’s attempt appears to have been an acceptable but not wild success as a little bit of fruitful discussion occurred. [sent-2, score-1.7]
3 I’m hoping this year will be a bit more of a success—please don’t be shy I’d like to also point out that ICML ‘s early registration deadline has a few hours left, while UAI ‘s and COLT ‘s are in a week. [sent-3, score-1.687]
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same-blog 1 0.99999988 356 hunch net-2009-05-24-2009 ICML discussion site
Introduction: Mark Reid has setup a discussion site for ICML papers again this year and Monica Dinculescu has linked it in from the ICML site. Last year’s attempt appears to have been an acceptable but not wild success as a little bit of fruitful discussion occurred. I’m hoping this year will be a bit more of a success—please don’t be shy I’d like to also point out that ICML ‘s early registration deadline has a few hours left, while UAI ‘s and COLT ‘s are in a week.
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Introduction: Mark Reid has stepped up and created a comment system for ICML papers which Greger Linden has tightly integrated. My understanding is that Mark spent quite a bit of time on the details, and there are some cool features like working latex math mode. This is an excellent chance for the ICML community to experiment with making ICML year-round, so I hope it works out. Please do consider experimenting with it.
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Introduction: Mark Reid did a post on ICML trends that I found interesting.
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Introduction: A substantial difficulty with the 2009 and 2008 ICML discussion system was a communication vacuum, where authors were not informed of comments, and commenters were not informed of responses to their comments without explicit monitoring. Mark Reid has setup a new discussion system for 2010 with the goal of addressing this. Mark didn’t want to make it to intrusive, so you must opt-in. As an author, find your paper and “Subscribe by email” to the comments. As a commenter, you have the option of providing an email for follow-up notification.
5 0.17990722 468 hunch net-2012-06-29-ICML survey and comments
Introduction: Just about nothing could keep me from attending ICML , except for Dora who arrived on Monday. Consequently, I have only secondhand reports that the conference is going well. For those who are remote (like me) or after the conference (like everyone), Mark Reid has setup the ICML discussion site where you can comment on any paper or subscribe to papers. Authors are automatically subscribed to their own papers, so it should be possible to have a discussion significantly after the fact, as people desire. We also conducted a survey before the conference and have the survey results now. This can be compared with the ICML 2010 survey results . Looking at the comparable questions, we can sometimes order the answers to have scores ranging from 0 to 3 or 0 to 4 with 3 or 4 being best and 0 worst, then compute the average difference between 2012 and 2010. Glancing through them, I see: Most people found the papers they reviewed a good fit for their expertise (-.037 w.r.t 20
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same-blog 1 0.98820668 356 hunch net-2009-05-24-2009 ICML discussion site
Introduction: Mark Reid has setup a discussion site for ICML papers again this year and Monica Dinculescu has linked it in from the ICML site. Last year’s attempt appears to have been an acceptable but not wild success as a little bit of fruitful discussion occurred. I’m hoping this year will be a bit more of a success—please don’t be shy I’d like to also point out that ICML ‘s early registration deadline has a few hours left, while UAI ‘s and COLT ‘s are in a week.
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Introduction: Mark Reid has stepped up and created a comment system for ICML papers which Greger Linden has tightly integrated. My understanding is that Mark spent quite a bit of time on the details, and there are some cool features like working latex math mode. This is an excellent chance for the ICML community to experiment with making ICML year-round, so I hope it works out. Please do consider experimenting with it.
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Introduction: Mark Reid did a post on ICML trends that I found interesting.
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Introduction: A substantial difficulty with the 2009 and 2008 ICML discussion system was a communication vacuum, where authors were not informed of comments, and commenters were not informed of responses to their comments without explicit monitoring. Mark Reid has setup a new discussion system for 2010 with the goal of addressing this. Mark didn’t want to make it to intrusive, so you must opt-in. As an author, find your paper and “Subscribe by email” to the comments. As a commenter, you have the option of providing an email for follow-up notification.
5 0.66792721 117 hunch net-2005-10-03-Not ICML
Introduction: Alex Smola showed me this ICML 2006 webpage. This is NOT the ICML we know, but rather some people at “Enformatika”. Investigation shows that they registered with an anonymous yahoo email account from dotregistrar.com the “Home of the $6.79 wholesale domain!” and their nameservers are by Turkticaret , a Turkish internet company. It appears the website has since been altered to “ ICNL ” (the above link uses the google cache). They say that imitation is the sincerest form of flattery, so the organizers of the real ICML 2006 must feel quite flattered.
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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
3 0.67165679 250 hunch net-2007-06-23-Machine Learning Jobs are Growing on Trees
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
4 0.64810467 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.
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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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