Research map / Label-efficient and robust learning / Domain adaptation and generalization
Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add discriminative structure loss (ablation) | DRMEA · VisDA-2017 synthetic→real | mean recognition rate (%): 71.1 -> 79.3 | Helped |
| add manifold metric alignment loss (ablation) | DRMEA · VisDA-2017 synthetic→real | mean recognition rate (%): 69.7 -> 79.3 | Helped |
| add discriminative structure loss (ablation) | DRMEA · Office-Home | mean recognition rate (%): 66.3 -> 68.1 | Helped |
| add manifold metric alignment loss (ablation) | DRMEA · Office-Home | mean recognition rate (%): 67.1 -> 68.1 | Helped |
| add discriminative structure loss (ablation) | DRMEA · Image-CLEF-DA | mean recognition rate (%): 86.8 -> 89.1 | Helped |
| add manifold metric alignment loss (ablation) | DRMEA · Image-CLEF-DA | mean recognition rate (%): 87.3 -> 89.1 | Helped |
Closest papers by meaning
- Unsupervised Domain Adaptation With Similarity Learning (CVPR 2018 · similarity 0.89)
- Representation Subspace Distance for Domain Adaptation Regression (ICML 2021 · similarity 0.89)
- Co-regularized Alignment for Unsupervised Domain Adaptation (NeurIPS 2018 · similarity 0.89)
- Unsupervised Domain Adaptation for Distance Metric Learning (ICLR 2019 · similarity 0.89)
- CASUAL: Conditional Support Alignment for Domain Adaptation with Label Shift (AAAI 2025 · similarity 0.87)
- Can We Evaluate Domain Adaptation Models Without Target-Domain Labels? (ICLR 2024 · similarity 0.86)
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