Research map / Learning theory and algorithms / Matrix and tensor methods
Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use RIGA instead of Oja's rule | online linear subspace estimation · Human body shape | reconstruction error: 16.8 mm -> 1.0 mm | Helped |
| use RIGA instead of EM-PCA | online linear subspace estimation · Human body shape | reconstruction error: 1.9 mm -> 1.0 mm | Helped |
| use RIGA instead of GROUSE | online linear subspace estimation · Human body shape | reconstruction error: 1.4 mm -> 1.0 mm | Helped |
| use RIGA instead of Oja's rule | online linear subspace estimation · Santa Claus Conquers the Martians | reconstruction error: 0.054 -> 0.023 | Helped |
| use RIGA instead of EM-PCA | online linear subspace estimation · Santa Claus Conquers the Martians | reconstruction error: 0.025 -> 0.023 | Helped |
| use RIGA instead of GROUSE | online linear subspace estimation · Santa Claus Conquers the Martians | reconstruction error: 0.023 -> 0.023 | No clear effect |
| use RRIGA instead of GRASTA or DHR-PCA | robust subspace estimation · UCSD anomaly detection (Peds1 and Peds2) | reconstruction error | Helped |
| use RRIGA instead of GRASTA or DHR-PCA | robust subspace estimation · Extended YaleB | reconstruction error | Mixed |
Closest papers by meaning
- Subspace Recovery from Heterogeneous Data with Non-isotropic Noise (NeurIPS 2022 · similarity 0.89)
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- Random features for Grassmannian kernel approximation with bounded rank-one projections (NeurIPS 2026 · similarity 0.86)
- A Geometric Analysis of PCA (NeurIPS 2025 · similarity 0.86)
- Efficient Sparse PCA via Block-Diagonalization (ICLR 2025 · similarity 0.86)
- Capturing the denoising effect of PCA via compression ratio (NeurIPS 2024 · similarity 0.86)
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