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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
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
Self-Adaptive Partial Domain Adaptation—0
Source Class Selection with Label Propagation for Partial Domain AdaptationCode0
Partial Domain Adaptation without Domain AlignmentCode0
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network—0
Partial Feature Selection and Alignment for Multi-Source Domain Adaptation—0
Domain Consensus Clustering for Universal Domain AdaptationCode0
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