Jan 31, 2014 · In this paper, we discuss a method for projecting both source and target data to a generalized subspace where each target sample can be represented by some ...
Generalized Transfer Subspace Learning Through Low-Rank ...
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Transfer subspace learning via low-rank and discriminative reconstruction matrix · Computer Science. Knowl. Based Syst. · 2019.
By employing a low-rank constraint during this transfer, the structure of source and target domains are preserved. This approach has three benefits. First, good ...
By employing a low-rank constraint during this transfer, the structure of source and target domains are preserved. This approach has three benefits. First, good ...
Generalized Transfer Subspace Learning Through Low-Rank Constraint. Language ... Transfer learning provides techniques for transferring learned knowledge ...
A new approach in unsupervised domain transfer learning is proposed. •. The low rank and sparse constraints are imposed on the reconstruction matrix.
@article{shao2014generalized, title={Generalized Transfer Subspace Learning through Low-Rank Constraint}, author={Shao, Ming and Kit, Dmitry and Fu, Yun ...
In this paper, we address the problem of unsupervised domain transfer learning in which no labels are available in the target domain.
Abstract. We consider an interesting problem in this paper that uses transfer learning in two directions to compensate missing knowledge from the target ...
In the paper, we present a new transfer subspace learning algorithm termed discriminative transfer regression (DTR) for cross-domain image recognition.