Research map / Learning theory and algorithms / Matrix and tensor methods
RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use RES-PCA instead of AltProj | RPCA · Bootstrap | time: 68.61 -> 16.73 | Helped |
| Use RES-PCA instead of AltProj | RPCA · Escalator Airport | time: 69.34 -> 20.47 | Helped |
| Use RES-PCA instead of AltProj | RPCA · Hall Airport | time: 93.62 -> 26.38 | Helped |
| Use RES-PCA instead of AltProj | RPCA · Highway | time: 119.17 -> 35.32 | Helped |
| Use RES-PCA instead of AltProj | RPCA · Shopping Mall | time: 85.92 -> 28.44 | Helped |
| Use RES-PCA instead of AltProj | RPCA · Lobby | time: 21.58 -> 20.11 | Helped |
| Use RES-PCA with an incorrect cluster count rather than AltProj with an incorrect rank | RPCA · Foreground-background separation with unknown rank | visual separation quality | Helped |
Closest papers by meaning
- Adaptive Rank Estimate in Robust Principal Component Analysis (CVPR 2021 · similarity 0.91)
- Efficient Robust Principal Component Analysis via Block Krylov Iteration and CUR Decomposition (CVPR 2023 · similarity 0.90)
- A Nonconvex Projection Method for Robust PCA (AAAI 2019 · similarity 0.89)
- Robust Principal Component Analysis with Side Information (ICML 2016 · similarity 0.89)
- Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization (CVPR 2016 · similarity 0.89)
- Efficient Sparse PCA via Block-Diagonalization (ICLR 2025 · similarity 0.87)
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