Feature extraction using constrained maximum variance mapping
- 30 November 2008
- journal article
- Published by Elsevier BV in Pattern Recognition
- Vol. 41 (11), 3287-3294
- https://doi.org/10.1016/j.patcog.2008.05.014
Abstract
No abstract availableThis publication has 29 references indexed in Scilit:
- Unsupervised Learning of Image Manifolds by Semidefinite ProgrammingInternational Journal of Computer Vision, 2006
- Local distance preservation in the GP-LVM through back constraintsPublished by Association for Computing Machinery (ACM) ,2006
- Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space AlignmentSIAM Journal on Scientific Computing, 2004
- Laplacian Eigenmaps for Dimensionality Reduction and Data RepresentationNeural Computation, 2003
- Hessian eigenmaps: Locally linear embedding techniques for high-dimensional dataProceedings of the National Academy of Sciences of the United States of America, 2003
- PCA versus LDAIEEE Transactions on Pattern Analysis and Machine Intelligence, 2001
- Nonlinear Dimensionality Reduction by Locally Linear EmbeddingScience, 2000
- A Global Geometric Framework for Nonlinear Dimensionality ReductionScience, 2000
- Nonlinear Component Analysis as a Kernel Eigenvalue ProblemNeural Computation, 1998
- Eigenfaces vs. Fisherfaces: recognition using class specific linear projectionIEEE Transactions on Pattern Analysis and Machine Intelligence, 1997