Research map / Learning theory and algorithms / Clustering
Optimal Neighborhood Kernel Clustering with Multiple Kernels
Read the paperCheck 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 |
|---|---|---|---|
| let optimal kernel lie in neighborhood of linear kernel combination (vs linear combination) | MKKM · psortPos | ACC: 60.81 -> 64.33 | Helped |
| neighborhood kernel vs MKKM-MR | multiple kernel k-means · warpPIE10P | ACC: 55.24 -> 81.43 | Helped |
| ONKC vs RMKKM | multiple kernel clustering · JAFFE | ACC: 84.51 -> 83.57 | Hurt |
| ONKC vs RMSC | multiple kernel clustering · TOX171 | NMI: 33.66 -> 28.91 | Hurt |
| vary rho (neighborhood size regularizer) (ablation) | ONKC · psortPos | ACC | Mixed |
| vary lambda over wide range (ablation) | ONKC · psortPos | ACC | No clear effect |
Closest papers by meaning
- Multiple Kernel k-Means Clustering with Matrix-Induced Regularization (AAAI 2016 · similarity 0.91)
- COKE: Core Kernel for More Efficient Approximation of Kernel Weights in Multiple Kernel Clustering (ICML 2025 · similarity 0.91)
- Incremental Nyström-based Multiple Kernel Clustering (AAAI 2025 · similarity 0.89)
- Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation (ICML 2024 · similarity 0.88)
- Efficient Constrained K-center Clustering with Background Knowledge (AAAI 2024 · similarity 0.86)
- Explaining Kernel Clustering via Decision Trees (ICLR 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.