gplrf
Gaussian Process Latent Random Field
Zhong, Guoqiang (Chinese Academy of Sciences) | Li, Wu-Jun (The Hong Kong University of Science and Technology) | Yeung, Dit-Yan (The Hong Kong University of Science and Technology) | Hou, Xinwen (Chinese Academy of Sciences) | Liu, Cheng-Lin (Chinese Academy of Sciences)
In this paper, we propose a novel supervised extension of GPLVM, called Gaussian process latent random field (GPLRF), by enforcing the latent variables to be a Gaussian Markov random field with respect to a graph constructed from the supervisory information.