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Partial Domain Adaptation

Partial Domain Adaptation is a transfer learning paradigm, which manages to transfer relevant knowledge from a large-scale source domain to a small-scale target domain.

Source: Deep Residual Correction Network for Partial Domain Adaptation

Papers

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Showing 31–40 of 56 papers

TitleStatusHype
On Evolving Attention Towards Domain Adaptation—0
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation—0
Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation—0
Adversarial Consistent Learning on Partial Domain Adaptation of PlantCLEF 2020 Challenge—0
Unsupervised Domain Adaptation with Progressive Adaptation of SubspacesCode0
Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation—0
Discriminative Cross-Domain Feature Learning for Partial Domain Adaptation—0
Learning Target Domain Specific Classifier for Partial Domain Adaptation—0
Associative Partial Domain Adaptation—0
Discriminative Partial Domain Adversarial Network—0
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