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.
Jul-15-2010
- Country:
- Asia > China
- Hong Kong (0.14)
- North America > United States (0.47)
- Asia > China
- Genre:
- Research Report > Experimental Study (0.46)
- Technology: