• Corpus ID: 220128104

# Transfer Learning via $\ell_1$ Regularization

@article{Takada2020TransferLV,
title={Transfer Learning via \$\ell\_1\$ Regularization},
journal={arXiv: Machine Learning},
year={2020}
}
• Published 1 June 2020
• Computer Science
• arXiv: Machine Learning
Machine learning algorithms typically require abundant data under a stationary environment. However, environments are nonstationary in many real-world applications. Critical issues lie in how to effectively adapt models under an ever-changing environment. We propose a method for transferring knowledge from a source domain to a target domain via $\ell_1$ regularization. We incorporate $\ell_1$ regularization of differences between source parameters and target parameters, in addition to an…

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