Active Learning - Revision history

Akshay at 15:59, 21 January 2015

2015-01-21T15:59:33Z

2015-01-21T15:58:00Z

2015-01-21T15:57:38Z

2015-01-21T15:51:32Z

2015-01-21T15:47:18Z

2015-01-21T15:29:23Z

2015-01-21T15:29:02Z

2015-01-21T15:27:34Z

2015-01-21T15:27:16Z

2015-01-21T15:20:21Z

← Older revision		Revision as of 15:59, 21 January 2015
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	The code below applies the proposed active learning method to [http://www.cs.nyu.edu/~roweis/data.html USPS Handwritten Digit Recognition dataset]. It is written in MATLAB R2013a. It uses the [http://wiki.epfl.ch/sgwt SGWT toolbox] which is also included.		The code below applies the proposed active learning method to [http://www.cs.nyu.edu/~roweis/data.html USPS Handwritten Digit Recognition dataset]. It is written in MATLAB R2013a. It uses the [http://wiki.epfl.ch/sgwt SGWT toolbox] which is also included.

		+	<br>

	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.		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.

@@ Line 21: / Line 21: @@
 The code below applies the proposed active learning method to [http://www.cs.nyu.edu/~roweis/data.html USPS Handwritten Digit Recognition dataset]. It is written in MATLAB R2013a. It uses the [http://wiki.epfl.ch/sgwt SGWT toolbox] which is also included.
-<ul>
 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.

@@ Line 19: / Line 19: @@
 <ul>
-The code below applies the proposed active learning method to [http://www.cs.nyu.edu/~roweis/data.html USPS Handwritten Digit Recognition dataset]. It is written in MATLAB R2013a. It uses the [http://wiki.epfl.ch/sgwt 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.
+The code below applies the proposed active learning method to [http://www.cs.nyu.edu/~roweis/data.html USPS Handwritten Digit Recognition dataset]. It is written in MATLAB R2013a. It uses the [http://wiki.epfl.ch/sgwt SGWT toolbox] which is also included.
 <ul>
 [http://sipi.usc.edu/~ortega/Papers/active-ssl-via-sampling-theory-code.zip  Active SSL via Sampling Theory Code]

@@ Line 19: / Line 19: @@
 <ul>
-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. 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.
+The code below applies the proposed active learning method to [http://www.cs.nyu.edu/~roweis/data.html USPS Handwritten Digit Recognition dataset]. It is written in MATLAB R2013a. It uses the [http://wiki.epfl.ch/sgwt 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>
 [http://sipi.usc.edu/~ortega/Papers/active-ssl-via-sampling-theory-code.zip  Active SSL via Sampling Theory Code]

@@ Line 19: / Line 19: @@
 <ul>
-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.
+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. 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>
 [http://sipi.usc.edu/~ortega/Papers/active-ssl-via-sampling-theory-code.zip  Active SSL via Sampling Theory Code]

← Older revision		Revision as of 15:29, 21 January 2015
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	<ul>		<ul>

−	[http://sipi.usc.edu/~ortega/Papers/active-ssl-via-sampling-theory-code.zip Active SSL via Sampling Theory]	+	[http://sipi.usc.edu/~ortega/Papers/active-ssl-via-sampling-theory-code.zip Active SSL via Sampling Theory Code]

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 <ul>
-<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.
+<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).
@@ Line 19: / Line 19: @@
 <ul>
-The code implements the active learning method proposed in The code is written in MATLAB R2013a.
+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.
 [http://sipi.usc.edu/~ortega/Papers/active-ssl-via-sampling-theory-code.zip  Matlab Code]