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Transfering Nonlinear Representations using Gaussian Processes with a Shared Latent Space
(2007-11-06)
When a series of problems are related, representations derived fromlearning earlier tasks may be useful in solving later problems. Inthis paper we propose a novel approach to transfer learning withlow-dimensional, non-linear ...
Transfer learning for image classification with sparse prototype representations
(2008-03-03)
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer learning which exploits available unlabeled ...