Feb 29, 2020 · In this paper, we make the first attempt to study OnTL with Multiple Source Domains for multi-class classification (MC), and propose an algorithm.
In this paper, we make the first attempt to study OnTL with Multiple Source Domains for multi-class classification (MC), and propose an algorithm, referred to ...
In this paper, we seek to promote classification performance in a target domain by leveraging labeled data from multiple source domains in online setting. To ...
In this paper, we seek to leverage labeled data from multiple source domains to enhance classification performance in a target domain where the target data are ...
OTLAMC learns a multi-class classifier in an online manner based on the knowledge from two sources, the obtained feedback of each datum in the target domain ...
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Jun 20, 2019 · I suggest using Data Stream algorithms to try on your problems since you are asking for "online learning with singular values or minibatches ...
In this paper, we seek to leverage labeled data from multiple source domains to enhance classification performance in a target domain where the target data are ...
This paper proposes novel online transfer learning paradigms in which the source and target domains are leveraged adaptively and works in an online manner, ...
Sep 10, 2024 · It's a pre-processing technique in which we augment the existing dataset with transformed versions of the existing images. We can perform ...
In this paper, we propose a new framework for transfer learning with multiple source domains. Specifically, in the proposed framework, we adopt autoencoders.