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       <dc:date>2009-11-23T14:46:55+08:00</dc:date>
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        <dc:date>2007-05-24T10:17:13+08:00</dc:date>
        <title>dmcase2007</title>
        <link>http://svm.csie.ntu.edu.tw/~svm/wiki/dmcase2007?rev=1179973033&amp;do=diff</link>
        <description>This is a place for instructor and students to record difficulties encountered during the course.



	*  Course Homepage
	*  NIPS 2003 Feature Selection Challenge  
	*  The results of post challenge entries are here:
		*  overall
		*  arcene
		*  gisette
		*  dexter
		*  dorothea
		*  madelon</description>
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        <dc:date>2007-03-08T22:15:59+08:00</dc:date>
        <title>paperpool</title>
        <link>http://svm.csie.ntu.edu.tw/~svm/wiki/paperpool?rev=1173363359&amp;do=diff</link>
        <description>Conference

	*  icml
	*  nips

Journal

	*  jmlr
	*  ieee tnn
	*  neural computation

Remove the paper if you selected.


	*  An evaluation of statistical approaches to text categorization (Y. Yang)
	*  A re-examination of text categorization methods (Y. Yang)
	*  Parallel sequential minimal optimization for the training of support vector machines</description>
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        <dc:date>2009-11-09T23:22:29+08:00</dc:date>
        <title>seminar</title>
        <link>http://svm.csie.ntu.edu.tw/~svm/wiki/seminar?rev=1257780149&amp;do=diff</link>
        <description>There are some papers collected HERE.  You may want to select paper from them.

2009 Fall

	*  9/25 (Fri.)  Scan presetns Chunking with Support Vector Machines.
	*  10/2 (Fri.)  Kai-Min presents Trust region Newton method for large-scale logistic regression
	*  10/9 (Fri.)  Chen-Tse presents his work
	*  10/16 (Fri.) GuoXun present his work.
	*  10/23 (Fri.) GuoXun present his work.
	*  10/30 (Fri.) OMG present ???. 
	*  11/6 (Fri.)  PoPo present Fast Logistic Regression for Text Categorization …</description>
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        <dc:date>2007-03-27T14:02:52+08:00</dc:date>
        <title>start</title>
        <link>http://svm.csie.ntu.edu.tw/~svm/wiki/start?rev=1174975372&amp;do=diff</link>
        <description>*  Seminar
	*  Lab Affairs

	*  Data Mining and Machine Learning Case Study 2007</description>
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