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Experimental Codes for Collaborative Filtering with Graph Information: Consistency and Scalable Methods.
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rofuyu/exp-grmf-nips15
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Requirement =========== - Unix-like Environment - Gnu GCC/G++ 4.8 or above - Matlab or Octave - If you are using Mac OS X, please install GCC and Octave via Mac HomeBrew Install ======= - Open a Matlab or Octave interactive terminal - type > install Usage ===== >> addpath('trmf-core/matlab') % or addpath('trmf-core/octave'); >> glr_mf_train Usage: [W' H' rmse walltime] = glr_mf_train(Y, testY, A, B [, 'options']) Usage: [W' H' rmse walltime] = glr_mf_train(Y, testY, A, B, W', H' [, 'options']) Y: [I J V] a nnz-by-3 matrix with each row as an entry in the observed matrix A: a symmetric sparse matrix, e.g., Laplacian for rows B: a symmetric sparse matrix, e.g., Laplacian for cols options: -n threads : set the number of threads (default 4) -k rank : set the rank (default 10) -e epsilon : set stopping criterion epsilon of tron (default 0.1) -t max_iter: set the number of iterations (default 10) -g max_cg_iter: set the number of iterations used in CG (default 5) -q verbose: show information or not (default 1) FAQ === - If you see something like "Invalid MEX-file ... libstdc++.so.6: version `CXXABI_1.3.8' not found..," the libstdc++ in your system is newer than the version that comes with matlab. You can resolve this problem by opening matlab with a LD_PRELOAD environment variable such as LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libstdc++.so.6 matlab Citation ======== Please acknowledge the use of the code with a citation. @InProceedings{ NR15a, title={Collaborative Filtering with Graph Information: Consistency and Scalable Methods}, author={Rao, Nikhil and Yu, Hsiang-Fu and Ravikumar, Pradeep K. and Dhillon, Inderjit S.}, booktitle = {Advances in Neural Information Processing Systems 27}, year={2015} } If you have any questions regarding the code, feel free to contact Hsiang-Fu Yu (rofuyu at cs utexas edu).
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