Research map / Label-efficient and robust learning / Recognition and long-tail
Unsupervised Correlation Analysis
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| remove the cycle constraint (ablation) | UCA · MNIST Halves | AUC: 0.67/0.67 -> 0.73/0.73 | Helped |
| remove the cycle constraint (ablation) | UCA · Birds | AUC: 0.74/0.74 -> 0.80/0.76 | Helped |
| remove the cycle constraint (ablation) | UCA · Flowers | AUC: 0.57/0.53 -> 0.60/0.59 | Helped |
| remove latent-domain confusion, orthogonality, and reconstruction losses (ablation) | UCA · Flickr8k | AUC: 0.51/0.50 -> 0.76/0.76 | Helped |
| remove latent-domain confusion, orthogonality, and reconstruction losses (ablation) | UCA · Birds | AUC: 0.74/0.74 -> 0.72/0.70 | Hurt |
| use the consensus-based run selection instead of an individual UCA variant (ablation) | UCA · Birds | AUC: 0.80/0.76 -> 0.86/0.83 | Helped |
| use the consensus-based run selection instead of an individual UCA variant (ablation) | UCA · Flickr8k | AUC: 0.76/0.76 -> 0.82/0.81; 0.68/0.68 -> 0.82/0.81 | Mixed |
| add the cycle constraint (ablation) | UCA · Flowers | AUC: 0.60/0.59 -> 0.57/0.53; 0.52/0.55 | Mixed |
Closest papers by meaning
- Linking Image and Text With 2-Way Nets (CVPR 2017 · similarity 0.90)
- Unpaired Canonical Correlation Analysis (NeurIPS 2026 · similarity 0.89)
- Correlational Gaussian Processes for Cross-Domain Visual Recognition (CVPR 2017 · similarity 0.88)
- Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning (ICLR 2024 · similarity 0.87)
- On Sparse Canonical Correlation Analysis (NeurIPS 2024 · similarity 0.87)
- Universal Domain Adaptation for Semantic Segmentation (CVPR 2025 · similarity 0.85)
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