文件名称:code-sparse
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稀疏矩阵分解算法,包括稀疏，流形学习，降噪，降维等-sparse matrix factorization algorithm
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下载文件列表
code sparse
...........\bestMap.m
...........\constructKernel.m
...........\constructW.m
...........\CSRKDApredict.m
...........\CSRKDAtrain.m
...........\Eigenmap.m
...........\EMR.m
...........\EMRtest.m
...........\ep1R.mexw32
...........\ep1R.mexw64
...........\EuDist2.m
...........\GenSpatialSmoothRegularizer.m
...........\GenTwoNoisyCircle.m
...........\getargs.m
...........\GNMF.m
...........\GNMF_KL.m
...........\GNMF_KL_Multi.m
...........\GNMF_Multi.m
...........\GraphSC.m
...........\hungarian.m
...........\initFactor.m
...........\IsoP.m
...........\KDA.m
...........\KGE.m
...........\KLPP.m
...........\KPCA.m
...........\KSR.m
...........\KSR_caller.m
...........\LaplacianScore.m
...........\LapPLSI.m
...........\lars.m
...........\LCCF.m
...........\LCCF_Multi.m
...........\LCGMM.m
...........\LDA.m
...........\learn_basis.m
...........\learn_coefficients.m
...........\LeastR.m
...........\LGE.m
...........\litekmeans.m
...........\LPP.m
...........\LSC.m
...........\LSDA.m
...........\lsqr2.m
...........\LTM.m
...........\MAED.m
...........\MAEDseq.m
...........\main2.m
...........\MCFS_p.m
...........\mex_EMstep.mexw32
...........\mex_EMstep.mexw64
...........\mex_logL.mexw32
...........\mex_logL.mexw64
...........\mex_Pw_d.mexw32
...........\mex_Pw_d.mexw64
...........\MMP.m
...........\MutualInfo.m
...........\mySVD.m
...........\NormalizeFea.m
...........\NPE.m
...........\OLGE.m
...........\OLPP.m
...........\PCA.m
...........\SCC.m
...........\SCCtest.m
...........\SDA.m
...........\sll_opts.m
...........\SparseCodingwithBasis.m
...........\SR.m
...........\SRDApredict.m
...........\SRDAtest.m
...........\SRDAtrain.m
...........\SRKDApredict.m
...........\SRKDAtest.m
...........\SRKDAtrain.m
...........\SR_caller.m
...........\TensorLGE.m
...........\TensorLPP.m
...........\TensorR_32x32.mat
...........\tfidf.m
...........\tuyale.m
...........\UKSRtest.m
...........\UKSRtrain.m
...........\USPS.mat
...........\USRtest.m
...........\USRtrain.m