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Found 5 papers, 2 papers with code
Against Adversarial Learning: Naturally Distinguish Known and Unknown in Open Set Domain Adaptation
Open set domain adaptation refers to the scenario that the target domain contains categories that do not exist in the source domain.
Mixed Set Domain Adaptation
Under the settings of MSDA, different categories of the source dataset are not all collected from the same domain(s).
Deep Adversarial Domain Adaptation Based on Multi-layer Joint Kernelized Distance
In this paper, a deep adversarial domain adaptation model based on a multi-layer joint kernelized distance metric is proposed.
Network Together: Node Classification via Cross-Network Deep Network Embedding
On the other hand, node attributes and labels are leveraged to capture the proximities between nodes across different networks by making the same labeled nodes across networks have aligned latent vector representations.
Network Together: Node Classification via Cross network Deep Network Embedding
On the other hand, node attributes and labels are leveraged to capture the proximities between nodes across different networks by making the same labeled nodes across networks have aligned latent vector representations.
Social and Information Networks
