hunch_net hunch_net-2009 hunch_net-2009-383 knowledge-graph by maker-knowledge-mining
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Introduction: I’d like to point out Inherent Uncertainty , which I’ve added to the ML blog post scanner on the right. My understanding from Jake is that the intention is to have a multiauthor blog which is more specialized towards learning theory/game theory than this one. Nevertheless, several of the posts seem to be of wider interest.
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same-blog 1 1.0 383 hunch net-2009-12-09-Inherent Uncertainty
Introduction: I’d like to point out Inherent Uncertainty , which I’ve added to the ML blog post scanner on the right. My understanding from Jake is that the intention is to have a multiauthor blog which is more specialized towards learning theory/game theory than this one. Nevertheless, several of the posts seem to be of wider interest.
2 0.2645365 225 hunch net-2007-01-02-Retrospective
Introduction: It’s been almost two years since this blog began. In that time, I’ve learned enough to shift my expectations in several ways. Initially, the idea was for a general purpose ML blog where different people could contribute posts. What has actually happened is most posts come from me, with a few guest posts that I greatly value. There are a few reasons I see for this. Overload . A couple years ago, I had not fully appreciated just how busy life gets for a researcher. Making a post is not simply a matter of getting to it, but rather of prioritizing between {writing a grant, finishing an overdue review, writing a paper, teaching a class, writing a program, etc…}. This is a substantial transition away from what life as a graduate student is like. At some point the question is not “when will I get to it?” but rather “will I get to it?” and the answer starts to become “no” most of the time. Feedback failure . This blog currently receives about 3K unique visitors per day from
3 0.19777873 137 hunch net-2005-12-09-Machine Learning Thoughts
Introduction: I added a link to Olivier Bousquet’s machine learning thoughts blog. Several of the posts may be of interest.
4 0.19758616 96 hunch net-2005-07-21-Six Months
Introduction: This is the 6 month point in the “run a research blog” experiment, so it seems like a good point to take stock and assess. One fundamental question is: “Is it worth it?” The idea of running a research blog will never become widely popular and useful unless it actually aids research. On the negative side, composing ideas for a post and maintaining a blog takes a significant amount of time. On the positive side, the process might yield better research because there is an opportunity for better, faster feedback implying better, faster thinking. My answer at the moment is a provisional “yes”. Running the blog has been incidentally helpful in several ways: It is sometimes educational. example More often, the process of composing thoughts well enough to post simply aids thinking. This has resulted in a couple solutions to problems of interest (and perhaps more over time). If you really want to solve a problem, letting the world know is helpful. This isn’t necessarily
5 0.19227095 151 hunch net-2006-01-25-1 year
Introduction: At the one year (+5 days) anniversary, the natural question is: “Was it helpful for research?” Answer: Yes, and so it shall continue. Some evidence is provided by noticing that I am about a factor of 2 more overloaded with paper ideas than I’ve ever previously been. It is always hard to estimate counterfactual worlds, but I expect that this is also a factor of 2 more than “What if I had not started the blog?” As for “Why?”, there seem to be two primary effects. A blog is a mechanism for connecting with people who either think like you or are interested in the same problems. This allows for concentration of thinking which is very helpful in solving problems. The process of stating things you don’t understand publicly is very helpful in understanding them. Sometimes you are simply forced to express them in a way which aids understanding. Sometimes someone else says something which helps. And sometimes you discover that someone else has already solved the problem. The
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same-blog 1 0.9896903 383 hunch net-2009-12-09-Inherent Uncertainty
Introduction: I’d like to point out Inherent Uncertainty , which I’ve added to the ML blog post scanner on the right. My understanding from Jake is that the intention is to have a multiauthor blog which is more specialized towards learning theory/game theory than this one. Nevertheless, several of the posts seem to be of wider interest.
2 0.79914474 480 hunch net-2013-03-22-I’m a bandit
Introduction: Sebastien Bubeck has a new ML blog focused on optimization and partial feedback which may interest people.
3 0.75961655 225 hunch net-2007-01-02-Retrospective
Introduction: It’s been almost two years since this blog began. In that time, I’ve learned enough to shift my expectations in several ways. Initially, the idea was for a general purpose ML blog where different people could contribute posts. What has actually happened is most posts come from me, with a few guest posts that I greatly value. There are a few reasons I see for this. Overload . A couple years ago, I had not fully appreciated just how busy life gets for a researcher. Making a post is not simply a matter of getting to it, but rather of prioritizing between {writing a grant, finishing an overdue review, writing a paper, teaching a class, writing a program, etc…}. This is a substantial transition away from what life as a graduate student is like. At some point the question is not “when will I get to it?” but rather “will I get to it?” and the answer starts to become “no” most of the time. Feedback failure . This blog currently receives about 3K unique visitors per day from
4 0.71646476 96 hunch net-2005-07-21-Six Months
Introduction: This is the 6 month point in the “run a research blog” experiment, so it seems like a good point to take stock and assess. One fundamental question is: “Is it worth it?” The idea of running a research blog will never become widely popular and useful unless it actually aids research. On the negative side, composing ideas for a post and maintaining a blog takes a significant amount of time. On the positive side, the process might yield better research because there is an opportunity for better, faster feedback implying better, faster thinking. My answer at the moment is a provisional “yes”. Running the blog has been incidentally helpful in several ways: It is sometimes educational. example More often, the process of composing thoughts well enough to post simply aids thinking. This has resulted in a couple solutions to problems of interest (and perhaps more over time). If you really want to solve a problem, letting the world know is helpful. This isn’t necessarily
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Introduction: David McAllester starts a blog .
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19 0.30523226 322 hunch net-2008-10-20-New York’s ML Day
20 0.29510006 250 hunch net-2007-06-23-Machine Learning Jobs are Growing on Trees
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1 0.97309512 467 hunch net-2012-06-15-Normal Deviate and the UCSC Machine Learning Summer School
Introduction: Larry Wasserman has started the Normal Deviate blog which I added to the blogroll on the right. Manfred Warmuth points out the UCSC machine learning summer school running July 9-20 which may be of particular interest to those in silicon valley.
same-blog 2 0.85156274 383 hunch net-2009-12-09-Inherent Uncertainty
Introduction: I’d like to point out Inherent Uncertainty , which I’ve added to the ML blog post scanner on the right. My understanding from Jake is that the intention is to have a multiauthor blog which is more specialized towards learning theory/game theory than this one. Nevertheless, several of the posts seem to be of wider interest.
3 0.74816954 200 hunch net-2006-08-03-AOL’s data drop
Introduction: AOL has released several large search engine related datasets. This looks like a pretty impressive data release, and it is a big opportunity for people everywhere to worry about search engine related learning problems, if they want.
4 0.74728185 121 hunch net-2005-10-12-The unrealized potential of the research lab
Introduction: I attended the IBM research 60th anniversary . IBM research is, by any reasonable account, the industrial research lab which has managed to bring the most value to it’s parent company over the long term. This can be seen by simply counting the survivors: IBM research is the only older research lab which has not gone through a period of massive firing. (Note that there are also new research labs .) Despite this impressive record, IBM research has failed, by far, to achieve it’s potential. Examples which came up in this meeting include: It took about a decade to produce DRAM after it was invented in the lab. (In fact, Intel produced it first.) Relational databases and SQL were invented and then languished. It was only under external competition that IBM released it’s own relational database. Why didn’t IBM grow an Oracle division ? An early lead in IP networking hardware did not result in IBM growing a Cisco division . Why not? And remember … IBM research is a s
5 0.6475082 142 hunch net-2005-12-22-Yes , I am applying
Introduction: Every year about now hundreds of applicants apply for a research/teaching job with the timing governed by the university recruitment schedule. This time, it’s my turn—the hat’s in the ring, I am a contender, etc… What I have heard is that this year is good in both directions—both an increased supply and an increased demand for machine learning expertise. I consider this post a bit of an abuse as it is neither about general research nor machine learning. Please forgive me this once. My hope is that I will learn about new places interested in funding basic research—it’s easy to imagine that I have overlooked possibilities. I am not dogmatic about where I end up in any particular way. Several earlier posts detail what I think of as a good research environment, so I will avoid a repeat. A few more details seem important: Application. There is often a tension between basic research and immediate application. This tension is not as strong as might be expected in my case. As
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