Research map / Learning theory and algorithms / Clustering
Exclusivity-Consistency Regularized Multi-View Subspace Clustering
Check your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add position-aware representation exclusivity (ablation) | ECMSC · Extended Yale-B | ACC: 0.692±0.013 -> 0.783±0.011 | Helped |
| Add indicator consistency (ablation) | ECMSC · Extended Yale-B | ACC: 0.678±0.010 -> 0.783±0.011 | Helped |
| Add position-aware representation exclusivity (ablation) | ECMSC · Yale | ACC: 0.742±0.008 -> 0.771±0.014 | Helped |
| Add indicator consistency (ablation) | ECMSC · Yale | ACC: 0.721±0.005 -> 0.771±0.014 | Helped |
| Add position-aware representation exclusivity (ablation) | ECMSC · ORL | ACC: 0.822±0.008 -> 0.854±0.011 | Helped |
| Add indicator consistency (ablation) | ECMSC · ORL | ACC: 0.841±0.012 -> 0.854±0.011 | Helped |
| Use position-aware exclusivity instead of value-aware HSIC diversity | Multi-view subspace clustering · Extended Yale-B | ACC: 0.615±0.003 -> 0.678±0.010 | Helped |
| Use position-aware exclusivity instead of value-aware HSIC diversity | Multi-view subspace clustering · Yale | ACC: 0.709±0.003 -> 0.721±0.005 | Helped |
| Use position-aware exclusivity instead of value-aware HSIC diversity | Multi-view subspace clustering · ORL | ACC: 0.838±0.001 -> 0.841±0.012 | No clear effect |
Closest papers by meaning
- Robust Consensus Anchor Learning for Efficient Multi-view Subspace Clustering (ICML 2025 · similarity 0.88)
- Scalable One-Pass Incomplete Multi-View Clustering by Aligning Anchors (AAAI 2025 · similarity 0.88)
- From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement (NeurIPS 2024 · similarity 0.87)
- Contrastive Multi-view Subspace Clustering via Tensor Transformers Autoencoder (AAAI 2025 · similarity 0.87)
- Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning (NeurIPS 2024 · similarity 0.86)
- Multi-View Clustering by Inter-cluster Connectivity Guided Reward (ICML 2024 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
