Active Learning
From WikiBiron
- A. Gadde, A. Anis and A. Ortega "Active Semi-Supervised Learning Using Sampling Theory for Graph Signals", KDD 2014, New York, USA, 2014.
- A. Anis, A. Gadde and A. Ortega "Towards a Sampling Theorem for Signals on Arbitrary Graphs", ICASSP 2014, Florence, Italy, 2014 (Best student paper award).
- S.K. Narang, A. Gadde and A. Ortega "Signal Processing Techniques for Interpolation of Graph Structured Data", ICASSP 2013, Vancouver, Canada, 2013.
- S.K. Narang, A. Gadde, E. Sanou and A. Ortega "Localized Iterative Methods for Interpolation of Graph Structured Data", GlobalSIP 2013, Austin, USA, 2013.
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The code below applies the proposed active learning method to USPS Handwritten Digit Recognition dataset. It is written in MATLAB R2013a. It uses the SGWT toolbox which is also included.
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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.
