Research map / Learning theory and algorithms / Clustering
Subspace Clustering via Variance Regularized Ridge Regression
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use VR3 instead of TRR | Subspace clustering · Extended Yale B, 10 subjects | clustering accuracy (%): 95.10 -> 98.85 | Helped |
| Use NVR3 instead of TRR | Subspace clustering · Alphadigits, 10 subjects | clustering accuracy (%): 68.38 -> 76.41 | Helped |
| Add adaptive manifold learning to VR3 (ablation) | VR3 · Extended Yale B, 2 subjects | clustering accuracy (%): 99.12 -> 99.07 | Hurt |
| Add adaptive manifold learning to VR3 (ablation) | VR3 · Extended Yale B, 10 subjects | clustering accuracy (%): 98.85 -> 99.38 | Helped |
| Add adaptive manifold learning to VR3 (ablation) | VR3 · Alphadigits, 10 subjects | clustering accuracy (%): 73.85 -> 76.41 | Helped |
| Tune the two manifold weights jointly (ablation) | NVR3 · Alphadigits | mean clustering accuracy | No clear effect |
Closest papers by meaning
- Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering (ICML 2022 · similarity 0.88)
- Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering (CVPR 2016 · similarity 0.88)
- Stochastic Sparse Subspace Clustering (CVPR 2020 · similarity 0.88)
- A Critique of Self-Expressive Deep Subspace Clustering (ICLR 2021 · similarity 0.88)
- Exploring a Principled Framework for Deep Subspace Clustering (ICLR 2025 · similarity 0.87)
- From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement (NeurIPS 2024 · similarity 0.87)
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