SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 21–30 of 56 papers

TitleStatusHype
On Evolving Attention Towards Domain Adaptation—0
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
Partial Feature Selection and Alignment for Multi-Source Domain Adaptation—0
Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network—0
Relation Adversarial Network for Low Resource Knowledge Graph Completion—0
Robust Class-Conditional Distribution Alignment for Partial Domain Adaptation—0
Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation—0
Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation—0
Show:102550
← PrevPage 3 of 6Next →

No leaderboard results yet.