文件名称:Matlab用半非负矩阵分解实现采样和协同过滤
文件大小:55.51MB
文件格式:ZIP
更新时间:2018-12-10 02:51:37
NMF CF 矩阵分解
Matlab用半非负矩阵分解实现采样和协同过滤 http://www.cnblogs.com/hxsyl/
【文件预览】:
semi-nmf-via-sampling-master
----figures()
--------likelihood_vs_sparsity_for_true_activations.pdf(8KB)
--------run1.pdf(60KB)
--------run1_respnorm_v2.pdf(61KB)
--------run2_respnorm.jpg(172KB)
--------run2_respnorm.pdf(61KB)
--------run3.pdf(60KB)
--------run4.pdf(60KB)
--------run3_respnorm_v2.pdf(60KB)
--------run1_respnorm.pdf(61KB)
--------loglik_vs_iteration.pdf(10KB)
--------run1.jpg(167KB)
--------run2_respnorm_v2.pdf(61KB)
--------run2.pdf(60KB)
--------response_profile_correlation_vs_iteration.pdf(10KB)
--------run4_respnorm_v2.pdf(59KB)
--------run5_respnorm_v2.pdf(60KB)
--------run1_respnorm.jpg(174KB)
--------run5.pdf(60KB)
--------response_profile_error_vs_iteration.pdf(10KB)
----tex()
--------semi_nmf_via_sampling.out(318B)
--------semi_nmf_via_sampling.pdf(142KB)
--------nips.sty(9KB)
--------semi_nmf_via_sampling.synctex.gz(26KB)
--------semi_nmf_via_sampling.aux(1KB)
--------semi_nmf_via_sampling.log(19KB)
--------semi_nmf_via_sampling.tex(7KB)
----code()
--------estimate_noise_from_repeated_measurements.m(2KB)
--------update_sparsity_fun.m(81B)
--------ResetRandStream2.m(400B)
--------removed_code.m(577B)
--------estimate_activations.m(4KB)
--------gradient_finite_differences.m(828B)
--------hessian_finite_differences.m(1KB)
--------update_activation_fun.m(555B)
--------estimate_noise_from_repeated_measurements.m~(1KB)
--------joint_log_likelihood.m(495B)
--------update_basis_fun.m(1KB)
--------rms.m(892B)
--------log_likelihood.m(755B)
--------estimate_response_profiles_and_sparsity.m(6KB)
----README.md(212B)
----test_code()
--------voxel_matrix_165x11065_centered.mat(39.75MB)
--------test_code_on_synthetic_dataset.m(1KB)
--------test_code_single_dimension.m(2KB)
--------sbatch()
--------ResetRandStream2.m(400B)
--------match_using_corrmatrix.m(407B)
--------export_fig()
--------results_from_synthetic_experiment.m(1KB)
--------results_from_synthetic_experiment_v2.m(2KB)
--------Hungarian.m(9KB)
--------results_from_synthetic_experiment_v3.m(4KB)
--------OLD()
--------ICA_scripts_v2()
--------test_code_on_synthetic_dataset_v2.m(963B)
--------test_code_on_synthetic_dataset_v3.m(1KB)
--------ICA_best_solution.mat(505KB)
--------synthetic_dataset.m(1KB)
--------synthetic_dataset.mat(13.83MB)