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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
Partial Distribution Matching via Partial Wasserstein Adversarial Networks—0
Partial Domain Adaptation Using Graph Convolutional Networks—0
Partial Domain Adaptation Using Selective Representation Learning For Class-Weight Computation—0
Implicit Semantic Response Alignment for Partial Domain AdaptationCode0
Importance Weighted Adversarial Nets for Partial Domain AdaptationCode0
Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain AdaptationCode0
Selective Partial Domain AdaptationCode0
Learning to Discover Knowledge: A Weakly-Supervised Partial Domain Adaptation ApproachCode0
From Big to Small: Adaptive Learning to Partial-Set DomainsCode0
Minimum Class Confusion for Versatile Domain AdaptationCode0
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