Feb 16, 2021 · Feature selection aims at choosing a subset of features to represent the original feature space. In practice, however, it is hard to achieve ...
In this paper, we study a new problem for feature selection named feature selection with multi-source transfer. To address this task, a novel method termed ...
May 1, 2022 · Feature selection aims at choosing a subset of features to represent the original feature space. In practice, however, it is hard to achieve ...
We propose a novel model termed Partial Feature Selection and Alignment (PFSA) to jointly cope with both MSDA and MSPDA tasks. Specifically, we firstly employ a ...
Feb 28, 2023 · In this paper, a new Multi-source transfer learning method based on Two-stage Weighted Fusion (MTWF) is proposed to improve classification accuracy in the ...
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Nov 28, 2023 · In this paper, we present a novel approach for addressing the FER problem using multi-source transfer learning.
Jun 17, 2023 · In this paper, we propose a novel multi-source transfer learning method based on the power set framework (PSF-MSTL), which can multiply combine ...
Common assumption in most machine learning algorithms is that, labeled (source) data and unlabeled (target) data are sampled from the same distribution.
May 7, 2022 · This paper proposes multi-source selection transfer learning algorithm with privacy-preserving MultiSTLP, which is used in scenarios where target domain ...
In this work, we embed transfer learning techniques into the widely used information criteria for feature selection and investigate the utility of the resulting ...