Difference between revisions of "Active Learning"

From WikiBiron
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<i>A. Gadde, A. Anis and A. Ortega "[http://sipi.usc.edu/~ortega/Papers/Gadde_KDD_14.pdf  Active Semi-Supervised Learning Using Sampling Theory for Graph Signals]",  <i>KDD 2014</i>,  New York, USA, 2014.
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<li>A. Gadde, A. Anis and A. Ortega "[http://sipi.usc.edu/~ortega/Papers/Gadde_KDD_14.pdf  Active Semi-Supervised Learning Using Sampling Theory for Graph Signals]",  <i>KDD 2014</i>,  New York, USA, 2014.
  
 
<LI>A. Anis, A. Gadde and A. Ortega "[http://sipi.usc.edu/~ortega/Papers/Anis_ICASSP_14.pdf  Towards a Sampling Theorem for Signals on Arbitrary Graphs]",  <i>ICASSP 2014</i>,  Florence, Italy, 2014 (Best student paper award).
 
<LI>A. Anis, A. Gadde and A. Ortega "[http://sipi.usc.edu/~ortega/Papers/Anis_ICASSP_14.pdf  Towards a Sampling Theorem for Signals on Arbitrary Graphs]",  <i>ICASSP 2014</i>,  Florence, Italy, 2014 (Best student paper award).
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The code implements the active learning method proposed in The code is written in MATLAB R2013a.  
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The code below applies the proposed active learning method to the USPS Handwritten Digit Recognition dataset. It is written in MATLAB R2013a. It uses the SGWT toolbox which is also included. To run the code, simply unpack the directory and run main_usps.m. If you have any questions, please email agadde at usc dot edu.
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[http://sipi.usc.edu/~ortega/Papers/active-ssl-via-sampling-theory-code.zip  Matlab Code]
 
[http://sipi.usc.edu/~ortega/Papers/active-ssl-via-sampling-theory-code.zip  Matlab Code]

Revision as of 08:27, 21 January 2015

  • Publications


  • Software
      The code below applies the proposed active learning method to the USPS Handwritten Digit Recognition dataset. It is written in MATLAB R2013a. It uses the SGWT toolbox which is also included. To run the code, simply unpack the directory and run main_usps.m. If you have any questions, please email agadde at usc dot edu. <\ul> Matlab Code