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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 41–50 of 56 papers

TitleStatusHype
Class Conditional Alignment for Partial Domain Adaptation—0
A Balanced and Uncertainty-aware Approach for Partial Domain AdaptationCode1
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain AdaptationCode1
Universal Domain Adaptation through Self SupervisionCode1
Minimum Class Confusion for Versatile Domain AdaptationCode0
Relation Adversarial Network for Low Resource Knowledge Graph Completion—0
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning—0
Tackling Partial Domain Adaptation with Self-Supervision—0
Discriminative Clustering for Robust Unsupervised Domain Adaptation—0
Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation—0
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