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)

Jul-15-2010–AAAI Conferences

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.

artificial intelligence, gplrf, machine learning, (18 more...)

AAAI Conferences

Jul-15-2010

Conferences PDF

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  - Statistical Learning (0.70)
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  - Inductive Learning (0.47)

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