Research map / Learning theory and algorithms / Clustering
Sparse Subspace Clustering with Entropy-Norm
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace SSC sparse optimization with Gaussian-kernel similarity (SSC+E) | spectral clustering similarity construction · ten benchmark data sets, runtime | clustering speed (seconds): e.g., COIL 70766.438 s (SSC) vs 0.534 s (SSC+E) at λ1 | Helped |
| Replace SSC sparse optimization with Gaussian-kernel similarity (SSC+E) | spectral clustering similarity construction · ten benchmark data sets, accuracy (ARI/NMI) | ARI/NMI | Mixed |
| Use Gaussian kernel instead of CAN optimization for similarity | spectral clustering similarity construction · ten benchmark data sets, runtime | clustering speed (seconds): slightly faster than CAN | Helped |
Closest papers by meaning
- Selective Sampling-based Scalable Sparse Subspace Clustering (NeurIPS 2019 · similarity 0.90)
- Theoretical Analysis of Sparse Subspace Clustering with Missing Entries (ICML 2018 · similarity 0.89)
- Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering (CVPR 2017 · similarity 0.89)
- Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds (CVPR 2016 · similarity 0.89)
- Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis (AAAI 2018 · similarity 0.88)
- Equivalence between Graph Spectral Clustering and Column Subset Selection (Student Abstract) (AAAI 2024 · similarity 0.85)
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