Locally Linear Generative Topographic Mapping
نویسندگان
چکیده
We propose a method for non-linear data projection that combines Generative Topographic Mapping and Coordinated PCA. We extend the Generative Topographic Mapping by using more complex nodes in the network: each node provides a linear map between the data space and the latent space. The location of a node in the data space is given by a smooth nonlinear function of its location in the latent space. Our model provides a piece-wise linear mapping between data and latent space, as opposed to the point-wise coupling of the Generative Topographic Mapping. We provide experimental results comparing this model with GTM.
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