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Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use UIMC instead of the strongest listed baseline | Incomplete multi-view classification · YaleB, η=0.5 | accuracy: 0.9692±0.03 -> 0.9769±0.01 | Helped |
| Use UIMC instead of the strongest listed baseline | Incomplete multi-view classification · ROSMAP, η=0.5 | accuracy: 0.6524±0.06 -> 0.7143±0.02 | Helped |
| Use UIMC instead of the strongest listed baseline | Incomplete multi-view classification · Handwritten, η=0.5 | accuracy: 0.9450±0.06 -> 0.9600±0.01 | Helped |
| Use UIMC instead of the strongest listed baseline | Incomplete multi-view classification · BRCA, η=0.5 | accuracy: 0.6714±0.04 -> 0.7429±0.02 | Helped |
| Use UIMC instead of the strongest listed baseline | Incomplete multi-view classification · Scene15, η=0.5 | accuracy: 0.6098±0.01 -> 0.6254±0.02 | Helped |
| Use multiple Gaussian-sampled imputations rather than one neighbor-mean imputation (ablation) | UIMC · Handwritten, YaleB, and Scene15 at η=[0, 0.1, 0.2, 0.3, 0.4, 0.5] | accuracy | Helped |
| Use uncertainty-guided evidential classification and fusion rather than cross-entropy classifiers (ablation) | UIMC · Handwritten, YaleB, and Scene15 at η=[0, 0.1, 0.2, 0.3, 0.4, 0.5] | accuracy | Helped |
Closest papers by meaning
- Enhancing Multi-View Classification Reliability with Adaptive Rejection (AAAI 2025 · similarity 0.89)
- Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding (AAAI 2024 · similarity 0.88)
- Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification (ICML 2025 · similarity 0.87)
- Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering (AAAI 2024 · similarity 0.87)
- Biased Incomplete Multi-View Learning (AAAI 2025 · similarity 0.87)
- Incomplete Multi-View Multi-Label Classification via Diffusion-Guided Redundancy Removal (AAAI 2025 · similarity 0.86)
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