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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 11–20 of 56 papers

TitleStatusHype
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods—0
Selective Partial Domain AdaptationCode0
Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation—0
OneRing: A Simple Method for Source-free Open-partial Domain AdaptationCode1
Controlled Generation of Unseen Faults for Partial and Open-Partial Domain Adaptation—0
From Big to Small: Adaptive Learning to Partial-Set DomainsCode0
Low-Cost On-device Partial Domain Adaptation (LoCO-PDA): Enabling efficient CNN retraining on edge devices—0
Implicit Semantic Response Alignment for Partial Domain AdaptationCode0
Adversarial Reweighting for Partial Domain AdaptationCode1
Self-Adaptive Partial Domain Adaptation—0
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