hunch_net hunch_net-2005 hunch_net-2005-108 knowledge-graph by maker-knowledge-mining
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Introduction: I read through some of the essays of Michael Nielsen today, and recommend them. Principles of Effective Research and Extreme Thinking are both relevant to several discussions here.
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same-blog 1 1.0 108 hunch net-2005-09-06-A link
Introduction: I read through some of the essays of Michael Nielsen today, and recommend them. Principles of Effective Research and Extreme Thinking are both relevant to several discussions here.
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Introduction: I wanted to point to Michael Nielsen’s talk about blogging science, which I found interesting.
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Introduction: I expect the NIPS 2006 workshops to be quite interesting, and recommend going for anyone interested in machine learning research. (Most or all of the workshops webpages can be found two links deep.)
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Introduction: I tweaked the site in a number of ways today, including: Updating to WordPress 1.5. Installing and heavily tweaking the Geekniche theme. Update: I switched back to a tweaked version of the old theme. Adding the Customizable Post Listings plugin. Installing the StatTraq plugin. Updating some of the links. I particularly recommend looking at the computer research policy blog. Adding threaded comments . This doesn’t thread old comments obviously, but the extra structure may be helpful for new ones. Overall, I think this is an improvement, and it addresses a few of my earlier problems . If you have any difficulties or anything seems “not quite right”, please speak up. A few other tweaks to the site may happen in the near future.
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Introduction: Machine Learning is a field with an impressively diverse set of reseearch styles. Understanding this may be important in appreciating what you see at a conference. Engineering . How can I solve this problem? People in the engineering research style try to solve hard problems directly by any means available and then describe how they did it. This is typical of problem-specific conferences and communities. Scientific . What are the principles for solving learning problems? People in this research style test techniques on many different problems. This is fairly common at ICML and NIPS. Mathematical . How can the learning problem be mathematically understood? People in this research style prove theorems with implications for learning but often do not implement (or test algorithms). COLT is a typical conference for this style. Many people manage to cross these styles, and that is often beneficial. Whenver we list a set of alternative, it becomes natural to think “wh
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Introduction: I read through some of the essays of Michael Nielsen today, and recommend them. Principles of Effective Research and Extreme Thinking are both relevant to several discussions here.
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Introduction: I wanted to point to Michael Nielsen’s talk about blogging science, which I found interesting.
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Introduction: Should results of experiments on proprietary datasets be in the academic research literature? The arguments I can imagine in the “against” column are: Experiments are not repeatable. Repeatability in experiments is essential to science because it allows others to compare new methods with old and discover which is better. It’s unfair. Academics who don’t have insider access to proprietary data are at a substantial disadvantage when competing with others who do. I’m unsympathetic to argument (2). To me, it looks like their are simply some resource constraints, and these should not prevent research progress. For example, we wouldn’t prevent publishing about particle accelerator experiments by physicists at CERN because physicists at CMU couldn’t run their own experiments. Argument (1) seems like a real issue. The argument for is: Yes, they are another form of evidence that an algorithm is good. The degree to which they are evidence is less than for public
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Introduction: I tweaked the site in a number of ways today, including: Updating to WordPress 1.5. Installing and heavily tweaking the Geekniche theme. Update: I switched back to a tweaked version of the old theme. Adding the Customizable Post Listings plugin. Installing the StatTraq plugin. Updating some of the links. I particularly recommend looking at the computer research policy blog. Adding threaded comments . This doesn’t thread old comments obviously, but the extra structure may be helpful for new ones. Overall, I think this is an improvement, and it addresses a few of my earlier problems . If you have any difficulties or anything seems “not quite right”, please speak up. A few other tweaks to the site may happen in the near future.
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Introduction: I found the article about science using modern tools interesting , especially the part about ‘blogophobia’, which in my experience is often a substantial issue: many potential guest posters aren’t quite ready, because of the fear of a permanent public mistake, because it is particularly hard to write about the unknown (the essence of research), and because the system for public credit doesn’t yet really handle blog posts. So far, science has been relatively resistant to discussing research on blogs. Some things need to change to get there. Public tolerance of the occasional mistake is essential, as is a willingness to cite (and credit) blogs as freely as papers. I’ve often run into another reason for holding back myself: I don’t want to overtalk my own research. Nevertheless, I’m slowly changing to the opinion that I’m holding back too much: the real power of a blog in research is that it can be used to confer with many people, and that just makes research work better.
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Introduction: I just presented the cross validation problem at COLT . The problem now has a cash prize (up to $500) associated with it—see the presentation for details. The write-up for colt .
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Introduction: I realized that the tools needed to solve the problem just posted were just created. I tried to sketch out the solution here (also in .lyx and .tex ). It is still quite sketchy (and probably only the few people who understand reductions well can follow). One of the reasons why I started this weblog was to experiment with “research in the open”, and this is an opportunity to do so. Over the next few days, I’ll be filling in details and trying to get things to make sense. If you have additions or ideas, please propose them.
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