LGE: (Regularized) Linear Graph Embedding (Provides a general framework for graph based subspace learning. This function will be called by LPP, NPE, IsoProjection, LSDA, MMP ...)
OLGE: (Regularized) Orthogonal Linear Graph Embedding (Provides a general framework for graph based subspace learning (orthogonal basis vectors). This function will be called by OLPP. It is also very easy to develop ONPE, OIsoProjection, OLSDA, MMP...)
TensorLGE: Tensor Linear Graph Embedding (Provides a general framework for graph based tensor subspace learning. This function will be called by TensorLPP. It is also very easy to develop TensorNPE, TensorIsoProjection, TensorLSDA, TensorMMP...)
KGE: (Regularized) Kernel Graph Embedding (Provides a general framework for graph based kernel subspace learning. This function will be called by KernelLPP. It is also very easy to develop KernelNPE, KernelIsoProjection, KernelLSDA, KernelMMP...)
Deng Cai, Xiaofei He and Jiawei Han, "Spectral Regression for Efficient Regularized Subspace Learning", ICCV'07. Bibtex source
Deng Cai, Xiaofei He, Yuxiao Hu, Jiawei Han and Thomas Huang, "Learning a Spatially
Smooth Subspace for Face Recognition", CVPR'07. Bibtex source
LDA: (Regularized) Linear Discriminant Analysis (Generally, LDA can also use LGE as a subroutine. However, we can use the special graph structure of LDA to obtain some computational benefits.)
KDA: (Regularized) Kernel Discriminant Analysis (Generally, KDA can also use KGE as a subroutine. However, we can use the special graph structure of KDA to obtain some computational benefits.)
Deng Cai, Xiaofei He and Jiawei Han, "SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis", IEEE TKDE 2008. Bibtex source
Deng Cai, Xiaofei He, Jiawei Han, "Speed Up Kernel Discriminant Analysis", The VLDB Journal, 2011. Bibtex source
LPP: Locality Preserving Projection (You need to download LGE.m as well as constructW.m).
OLPP: Orthogonal Locality Preserving Projections (You need to download OLGE.m as well as constructW.m)
TensorLPP: Tensor Locality Preserving Projections (You need to download TensorLGE.m as well as constructW.m)
KernelLPP: Kernel Locality Preserving Projections (You need to download KGE.m as well as constructW.m)
Deng Cai, Xiaofei He, Jiawei Han, and Hong-Jiang Zhang, "Orthogonal Laplacianfaces for Face Recognition", in IEEE TIP, 2006. Bibtex source
Xiaofei He, Deng Cai, and Partha Niyogi, "Tensor Subspace Analysis", NIPS 2005. Bibtex source
Xiaofei He, Shuicheng Yan, Yuxiao Hu, Partha Niyogi, and Hong-Jiang Zhang, "Face Recognition Using Laplacianfaces", in IEEE TPAMI, 2005. Bibtex source
Xiaofei He and Partha Niyogi, "Locality Preserving Projections", NIPS 16, 2003. Bibtex source
NPE: Neighborhood Preserving Embedding (You need to download LGE.m)
Xiaofei He, Deng Cai, Shuicheng Yan and Hong-Jiang Zhang, "Neighborhood Preserving Embedding," ICCV 2005. Bibtex source
IsoProjection: Isometric Projection (You need to download LGE.m)