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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
Self-Adaptive Partial Domain Adaptation—0
Self-Supervised Learning Across Domains—0
Soft-Masked Semi-Dual Optimal Transport for Partial Domain Adaptation—0
Tackling Partial Domain Adaptation with Self-Supervision—0
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning—0
TWINs: Two Weighted Inconsistency-reduced Networks for Partial Domain Adaptation—0
Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization—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
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