Transferring Nonlinear Representations using Gaussian Processes with a Shared Latent Space
When a series of problems are related, representations derived from learning earlier tasks may be useful in solving later problems. In this paper we propose a novel approach to transfer learning with low-dimensional, non-linear latent spaces. We show how such representations can be jointly learned a...
| Main Authors: | , , , |
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| Other Authors: | |
| Published: |
2008
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| Online Access: | http://hdl.handle.net/1721.1/41517 |