hunch_net hunch_net-2006 hunch_net-2006-212 knowledge-graph by maker-knowledge-mining
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Introduction: Aaron Hertzmann points out the health of conferences wiki , which has a great deal of information about how many different conferences function.
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same-blog 1 1.0 212 hunch net-2006-10-04-Health of Conferences Wiki
Introduction: Aaron Hertzmann points out the health of conferences wiki , which has a great deal of information about how many different conferences function.
2 0.12461934 81 hunch net-2005-06-13-Wikis for Summer Schools and Workshops
Introduction: Chicago ’05 ended a couple of weeks ago. This was the sixth Machine Learning Summer School , and the second one that used a wiki . (The first was Berder ’04, thanks to Gunnar Raetsch.) Wikis are relatively easy to set up, greatly aid social interaction, and should be used a lot more at summer schools and workshops. They can even be used as the meeting’s webpage, as a permanent record of its participants’ collaborations — see for example the wiki/website for last year’s NVO Summer School . A basic wiki is a collection of editable webpages, maintained by software called a wiki engine . The engine used at both Berder and Chicago was TikiWiki — it is well documented and gets you something running fast. It uses PHP and MySQL, but doesn’t require you to know either. Tikiwiki has far more features than most wikis, as it is really a full Content Management System . (My thanks to Sebastian Stark for pointing this out.) Here are the features we found most useful: Bulletin boa
3 0.11438876 217 hunch net-2006-11-06-Data Linkage Problems
Introduction: Data linkage is a problem which seems to come up in various applied machine learning problems. I have heard it mentioned in various data mining contexts, but it seems relatively less studied for systemic reasons. A very simple version of the data linkage problem is a cross hospital patient record merge. Suppose a patient (John Doe) is admitted to a hospital (General Health), treated, and released. Later, John Doe is admitted to a second hospital (Health General), treated, and released. Given a large number of records of this sort, it becomes very tempting to try and predict the outcomes of treatments. This is reasonably straightforward as a machine learning problem if there is a shared unique identifier for John Doe used by General Health and Health General along with time stamps. We can merge the records and create examples of the form “Given symptoms and treatment, did the patient come back to a hospital within the next year?” These examples could be fed into a learning algo
4 0.1007174 89 hunch net-2005-07-04-The Health of COLT
Introduction: The health of COLT (Conference on Learning Theory or Computational Learning Theory depending on who you ask) has been questioned over the last few years. Low points for the conference occurred when EuroCOLT merged with COLT in 2001, and the attendance at the 2002 Sydney COLT fell to a new low. This occurred in the general context of machine learning conferences rising in both number and size over the last decade. Any discussion of why COLT has had difficulties is inherently controversial as is any story about well-intentioned people making the wrong decisions. Nevertheless, this may be worth discussing in the hope of avoiding problems in the future and general understanding. In any such discussion there is a strong tendency to identify with a conference/community in a patriotic manner that is detrimental to thinking. Keep in mind that conferences exist to further research. My understanding (I wasn’t around) is that COLT started as a subcommunity of the computer science
5 0.093587048 21 hunch net-2005-02-17-Learning Research Programs
Introduction: This is an attempt to organize the broad research programs related to machine learning currently underway. This isn’t easy—this map is partial, the categories often overlap, and there are many details left out. Nevertheless, it is (perhaps) helpful to have some map of what is happening where. The word ‘typical’ should not be construed narrowly here. Learning Theory Focuses on analyzing mathematical models of learning, essentially no experiments. Typical conference: COLT. Bayesian Learning Bayes law is always used. Focus on methods of speeding up or approximating integration, new probabilistic models, and practical applications. Typical conferences: NIPS,UAI Structured learning Predicting complex structured outputs, some applications. Typiical conferences: NIPS, UAI, others Reinforcement Learning Focused on ‘agent-in-the-world’ learning problems where the goal is optimizing reward. Typical conferences: ICML Unsupervised Learning/Clustering/Dimensionality Reduc
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Introduction: Aaron Hertzmann points out the health of conferences wiki , which has a great deal of information about how many different conferences function.
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Introduction: I’d like to point out Yisong Yue ‘s post on Self-improving systems , which is a nicely readable description of the necessity and potential of interactive learning to deal with the information overload problem that is endemic to the modern internet.
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Introduction: Eric Zaetsch points out KDNuggets which is a well-developed mailing list/news site with a KDD flavor. This might particularly interest people looking for industrial jobs in machine learning, as the mailing list has many such.
4 0.4495067 270 hunch net-2007-11-02-The Machine Learning Award goes to …
Introduction: Perhaps the biggest CS prize for research is the Turing Award , which has a $0.25M cash prize associated with it. It appears none of the prizes so far have been for anything like machine learning (the closest are perhaps database awards). In CS theory, there is the Gödel Prize which is smaller and newer, offering a $5K prize along and perhaps (more importantly) recognition. One such award has been given for Machine Learning, to Robert Schapire and Yoav Freund for Adaboost. In Machine Learning, there seems to be no equivalent of these sorts of prizes. There are several plausible reasons for this: There is no coherent community. People drift in and out of the central conferences all the time. Most of the author names from 10 years ago do not occur in the conferences of today. In addition, the entire subject area is fairly new. There are at least a core group of people who have stayed around. Machine Learning work doesn’t last Almost every paper is fo
5 0.44142833 93 hunch net-2005-07-13-“Sister Conference” presentations
Introduction: Some of the “sister conference” presentations at AAAI have been great. Roughly speaking, the conference organizers asked other conference organizers to come give a summary of their conference. Many different AI-related conferences accepted. The presenters typically discuss some of the background and goals of the conference then mention the results from a few papers they liked. This is great because it provides a mechanism to get a digested overview of the work of several thousand researchers—something which is simply available nowhere else. Based on these presentations, it looks like there is a significant component of (and opportunity for) applied machine learning in AIIDE , IUI , and ACL . There was also some discussion of having a super-colocation event similar to FCRC , but centered on AI & Learning. This seems like a fine idea. The field is fractured across so many different conferences that the mixing of a supercolocation seems likely helpful for research.
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Introduction: his blog on information markets and other research topics .
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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: Aaron Hertzmann points out the health of conferences wiki , which has a great deal of information about how many different conferences function.
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