Partial Domain Adaptation
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Benchmarks
Most implemented
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Minimum Class Confusion for Versatile Domain Adaptation
Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation
Selective Partial Domain Adaptation
Improving Mini-batch Optimal Transport via Partial Transportation
Partial Adversarial Domain Adaptation
Papers
Take It or Leave It: Intent-Controlled Partial Optimal Transport
While optimal transport (OT) enforces a rigid constraint by requiring two measures to be matched exactly, partial optimal transport relaxes this requirement by allowing mass to remain unmatched through a global budget, s…
Partial Domain AdaptationPartial Domain Adaptation via Importance Sampling-based Shift Correction
Partial domain adaptation (PDA) is a challenging task in real-world machine learning scenarios. It aims to transfer knowledge from a labeled source domain to a related unlabeled target domain, where the support set of th…
Partial Domain AdaptationBi-level Unbalanced Optimal Transport for Partial Domain Adaptation
Partial domain adaptation (PDA) problem requires aligning cross-domain samples while distinguishing the outlier classes for accurate knowledge transfer. The widely used weighting framework tries to address the outlier cl…
Domain AdaptationPartial Domain AdaptationTransfer LearningSoft-Masked Semi-Dual Optimal Transport for Partial Domain Adaptation
Visual domain adaptation aims to learn discriminative and domain-invariant representation for an unlabeled target domain by leveraging knowledge from a labeled source domain. Partial domain adaptation (PDA) is a general …
Domain AdaptationPartial Domain AdaptationCo-training partial domain adaptation networks for industrial Fault Diagnosis
The partial domain adaptation (PDA) challenge is a prevalent issue in industrial fault diagnosis. Drawing inspiration from traditional classification settings where such partial challenge is not a concern, we propose a n…
Domain AdaptationFault DiagnosisPartial Domain AdaptationPartial Distribution Matching via Partial Wasserstein Adversarial Networks
This paper studies the problem of distribution matching (DM), which is a fundamental machine learning problem seeking to robustly align two probability distributions. Our approach is established on a relaxed formulation,…
Domain AdaptationPartial Domain Adaptation