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    <title>Machine Learning Thoughts</title>
    
    <link rel="alternate" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/" />
    <id>tag:typepad.com,2003:weblog-176291</id>
    <updated>2007-02-03T18:43:00+01:00</updated>
    <subtitle>Some thoughts about philosophical, theoretical and practical aspects of Machine Learning.</subtitle>
    <generator uri="http://www.typepad.com/">TypePad</generator>
    <atom10:link xmlns:atom10="http://www.w3.org/2005/Atom" rel="self" type="application/atom+xml" href="http://feeds.feedburner.com/MachineLearningThoughts" /><feedburner:info uri="machinelearningthoughts" /><atom10:link xmlns:atom10="http://www.w3.org/2005/Atom" rel="hub" href="http://pubsubhubbub.appspot.com/" /><feedburner:browserFriendly>This is an XML content feed. It is intended to be viewed in a newsreader or syndicated to another site, subject to copyright and fair use.</feedburner:browserFriendly><entry>
        <title>Happiness of a scientist III: testing ideas</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/3QxH81j6gNs/happiness_of_a__2.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2007/02/happiness_of_a__2.html" thr:count="35" thr:updated="2011-09-21T14:17:28+02:00" />
        <id>tag:typepad.com,2003:post-30015386</id>
        <published>2007-02-03T18:43:00+01:00</published>
        <updated>2007-02-03T18:43:00+01:00</updated>
        <summary>If you like rationalizing events (see Happiness of a scientist I), you would probably enjoy convincing yourself that your jobs actually fits with your initial expectations, and this will require a certain amount of rationalization and a posteriori reinterpretation of...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="Personal" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2007/02/happiness_of_a__2.html</feedburner:origLink></entry>
    <entry>
        <title>Happiness of a scientist II: the 80/20 rule</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/AjZx3PT2Pdg/happiness_of_a__1.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2007/02/happiness_of_a__1.html" thr:count="17" thr:updated="2012-01-14T15:54:12+01:00" />
        <id>tag:typepad.com,2003:post-30014798</id>
        <published>2007-02-03T18:20:07+01:00</published>
        <updated>2007-02-03T18:20:07+01:00</updated>
        <summary>Having tried to do scientific research at several different places, I have observed the following, which has been confirmed by several colleagues: No matter where you are, it is almost impossible to spend more than 20% of your time doing...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="Personal" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2007/02/happiness_of_a__1.html</feedburner:origLink></entry>
    <entry>
        <title>Happiness of a scientist I: rationalization</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/3lKq4SzFMiY/happiness_of_a_.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2007/02/happiness_of_a_.html" thr:count="6" thr:updated="2011-12-08T11:44:10+01:00" />
        <id>tag:typepad.com,2003:post-30013964</id>
        <published>2007-02-03T17:49:48+01:00</published>
        <updated>2007-02-03T17:49:48+01:00</updated>
        <summary>This post is a first of a series of somewhat personal posts. This will not be about Machine Learning in particular, nor will it be about science, but rather about scientists, their life and their quest for happiness. I often...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="Personal" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2007/02/happiness_of_a_.html</feedburner:origLink></entry>
    <entry>
        <title>The Failure of AI</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/jxVUP541UlQ/the_failure_of_.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2006/11/the_failure_of_.html" thr:count="45" thr:updated="2012-01-12T08:20:51+01:00" />
        <id>tag:typepad.com,2003:post-12758107</id>
        <published>2006-11-30T23:27:17+01:00</published>
        <updated>2006-11-30T23:27:17+01:00</updated>
        <summary>In the early days of AI, scientists thought they would be able to build an intelligent computer by the end of the 20th century. This raised various fears about computers eventually taking over the world, and human beings replaced by...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="Artificial Intelligence" />
        <category scheme="http://www.sixapart.com/ns/types#category" term="Data Mining" />
        <category scheme="http://www.sixapart.com/ns/types#category" term="Machine Learning" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2006/11/the_failure_of_.html</feedburner:origLink></entry>
    <entry>
        <title>Machine Learning Search Engine</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/p7bG5q1oHq4/machine_learnin_1.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2006/11/machine_learnin_1.html" thr:count="29" thr:updated="2011-11-24T18:59:51+01:00" />
        <id>tag:typepad.com,2003:post-14390860</id>
        <published>2006-11-30T22:36:33+01:00</published>
        <updated>2006-11-30T22:36:33+01:00</updated>
        <summary>Google custom search engines are a very nice idea. I have started to create such a custom search engine for Machine Learning research. It is still preliminary, so feel free to suggest URLs or categories to add to it. Here...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="Machine Learning" />
        <category scheme="http://www.sixapart.com/ns/types#category" term="search engine" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2006/11/machine_learnin_1.html</feedburner:origLink></entry>
    <entry>
        <title>Machine Learning Videos</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/ck_bKW9eavI/machine_learnin.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2006/11/machine_learnin.html" thr:count="43" thr:updated="2011-10-12T15:39:25+02:00" />
        <id>tag:typepad.com,2003:post-14339254</id>
        <published>2006-11-28T13:01:35+01:00</published>
        <updated>2006-11-28T13:01:35+01:00</updated>
        <summary>I have just created a page with a selection of cool Machine Learning videos (mainly talks given at Google). Feel free to suggest some more to add to this page...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="Machine Learning" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2006/11/machine_learnin.html</feedburner:origLink></entry>
    <entry>
        <title>Winning The DARPA Grand Challenge</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/h12u1EmJdVA/winning_the_dar.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2006/09/winning_the_dar.html" thr:count="5" thr:updated="2011-06-23T09:52:59+02:00" />
        <id>tag:typepad.com,2003:post-12499509</id>
        <published>2006-09-01T00:24:34+02:00</published>
        <updated>2006-09-01T00:24:34+02:00</updated>
        <summary>A very nice talk by Sebastian Thrun about how he and his team designed an autonomous driving vehicle for the DARPA Grand Challenge. What is interesting is the use of Machine Learning to train the program.</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2006/09/winning_the_dar.html</feedburner:origLink></entry>
    <entry>
        <title>Making Machine Learning More Scientific</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/dvDrO6Do2D8/making_machine_.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2006/06/making_machine_.html" thr:count="39" thr:updated="2011-10-11T11:40:32+02:00" />
        <id>tag:typepad.com,2003:post-10060431</id>
        <published>2006-06-20T23:14:27+02:00</published>
        <updated>2006-06-20T23:14:27+02:00</updated>
        <summary>The title of this post may seem awkward as most people working on ML would consider themselves as scientists. However, ML is still a young field, and as most scientific fields in their youth, the methods and practices are still...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="Machine Learning" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2006/06/making_machine_.html</feedburner:origLink></entry>
    <entry>
        <title>Learning Theory disconnected from Practice?</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/v3sCpOXSfdc/learning_theory.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2006/06/learning_theory.html" thr:count="6" thr:updated="2011-05-31T08:31:22+02:00" />
        <id>tag:typepad.com,2003:post-11139538</id>
        <published>2006-06-19T11:57:46+02:00</published>
        <updated>2006-06-19T11:57:46+02:00</updated>
        <summary>Is learning theory really answering the right questions? More precisely, does working on (statistical) learning theory bounds really help designing better algorithms? Let me first say that this note is not against anyone in particular. I know most of the...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="Theory" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2006/06/learning_theory.html</feedburner:origLink></entry>
    <entry>
        <title>Learning abilities of computers and humans</title>
        <link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/MachineLearningThoughts/~3/xs5cENgjG4A/learning_abilit.html" />
        <link rel="replies" type="text/html" href="http://ml.typepad.com/machine_learning_thoughts/2006/06/learning_abilit.html" thr:count="16" thr:updated="2011-11-24T20:22:26+01:00" />
        <id>tag:typepad.com,2003:post-11047510</id>
        <published>2006-06-14T16:39:59+02:00</published>
        <updated>2006-06-14T16:39:59+02:00</updated>
        <summary>While commenting on the comments to my previous note (see here), I thought about the comparison of human and computers in terms of learning performance. Does this comparison even make sense? If it does, on which basis, or with which...</summary>
        <author>
            <name>Olivier Bousquet</name>
        </author>
        <category scheme="http://www.sixapart.com/ns/types#category" term="General" />
        
        



    <feedburner:origLink>http://ml.typepad.com/machine_learning_thoughts/2006/06/learning_abilit.html</feedburner:origLink></entry>
 
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