####Terms of Use Copyright (c) 2009-2011 by by DVMM Laboratory
Department of Electrical Engineering
Columbia University
Rm 1312 S.W. Mudd, 500 West 120th Street
New York, NY 10027
USA
If it is your intention to use this code for non-commercial purposes, such as in academic research, this code is free.
If you use this code in your research, please acknowledge the authors, and cite our related publication:
Wei Liu, Junfeng He, and Shih-Fu Chang, "Large Graph Construction for Scalable Semi-Supervised Learning," International Conference on Machine Learning (ICML), Haifa, Israel, 2010.
####Instruction
Please first see usps_demo.m to find how my codes work.
To run AnchorGraph.m, one needs to input anchors. In my ICML'10 paper, I used K-means clustering centers as anchors. If one had any sophisticated or task specific clustering algorithms, it could be better to feed the resulting clustering centers to anchors. Nevertheless, I found K-means anchors are sufficiently good.
Another possible issue is dimensionality. I strongly suggest users to conduct dimension reduction such as PCA or LSA before running AnchorGraph.m. The proper dimension for data on which AnchorGraph is to be constructed is 100-1000.
For any problem with my codes, feel free to drop me a message via wliu@ee.columbia.edu. Also, I hope you to cite my ICML'10 paper in your publications.
Wei Liu April 18, 2011