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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 21–30 of 56 papers

TitleStatusHype
Robust Class-Conditional Distribution Alignment for Partial Domain Adaptation—0
Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation—0
Adversarial Consistent Learning on Partial Domain Adaptation of PlantCLEF 2020 Challenge—0
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods—0
A Robust Negative Learning Approach to Partial Domain Adaptation Using Source Prototypes—0
Associative Partial Domain Adaptation—0
A Unified Framework for Unsupervised Domain Adaptation based on Instance Weighting—0
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network—0
Relation Adversarial Network for Low Resource Knowledge Graph Completion—0
Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation—0
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