Twin Kernel Embedding with Back Constraints

Abstract

Twin kernel embedding (TKE) is a novel approach for visualization of non-vectorial objects. It preserves the similarity structure in high-dimensional or structured input data and reproduces it in a low dimensional latent space by matching the similarity relations represented by two kernel gram matrices, one kernel for the input data and the other for… (More)
DOI: 10.1109/ICDMW.2007.15

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Cite this paper

@article{Qiao2007TwinKE, title={Twin Kernel Embedding with Back Constraints}, author={Mengyun Qiao and Paul Wing Hing Kwan and Junbin Gao}, journal={Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007)}, year={2007}, pages={319-324} }