Research map / Learning theory and algorithms / Clustering
Deep Embedded Non-Redundant Clustering
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| jointly train non-linear autoencoder embedding with non-redundant clustering (ENRC) vs linear subspace baseline Nr-Kmeans on fixed autoencoder embedding | Nr-Kmeans · NR-Objects color | NMI: 0.92 -> 1.00 | Helped |
| joint transformation (ENRC) vs Nr-Kmeans | Nr-Kmeans · C-MNIST left | NMI: 0.69 -> 0.83 | Helped |
| joint transformation (ENRC) vs Nr-Kmeans | Nr-Kmeans · GTSRB type | NMI: 0.72 -> 0.74 | Helped |
| joint transformation (ENRC) vs Nr-Kmeans | Nr-Kmeans · Stickfigures | NMI: 1.00 -> 1.00 | No clear effect |
| ENRC vs Nr-Kmeans on redundancy between found clusterings | Nr-Kmeans · NR-Objects, GTSRB, Stickfigures, C-MNIST | VI: 2.39 vs 2.35 (NR-Objects) | No clear effect |
| sequential Orth1 vs parallel joint extraction (ENRC) | Orth1 · NR-Objects shape | NMI: 0.39 -> 1.00 | Helped |
Closest papers by meaning
- Unsupervised Deep Embedding for Clustering Analysis (ICML 2016 · similarity 0.89)
- DeepDPM: Deep Clustering With an Unknown Number of Clusters (CVPR 2022 · similarity 0.87)
- Bifurcate then Alienate: Incomplete Multi-view Clustering via Coupled Distribution Learning with Linear Overhead (ICML 2025 · similarity 0.85)
- Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation (AAAI 2024 · similarity 0.85)
- Deep Variational Incomplete Multi-View Clustering: Exploring Shared Clustering Structures (AAAI 2024 · similarity 0.85)
- Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models (ICLR 2024 · similarity 0.84)
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