Research map / Learning theory and algorithms / Matrix and tensor methods
Low-Rank-Sparse Subspace Representation for Robust Regression
Check 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 |
|---|---|---|---|
| Use LRS-RR's supervised low-rank-sparse subspace representation instead of LR-RR | robust regression · Synthetic data | RAE_T: 0.035 ± 0.015 -> 0.005 ± 0.0005 | Helped |
| Use LRS-RR's supervised low-rank-sparse subspace representation instead of LR-RR | robust regression · Synthetic data | RAE_Y: 0.015 ± 0.006 -> 0.011 ± 0.003 | Helped |
| Use LRS-RR instead of LR-RR | head pose estimation · CMU PIE subset | Pose Angle Err: 1.97o ± 5.77o -> 1.03o ± 5.65o | Helped |
| Use LRS-RR instead of LR-RR | head pose estimation · CMU PIE subset | Time(s): 3.03 -> 10.02 | Hurt |
| Use LRS-RR instead of the best listed baseline | robust regression · YaleB | Model Err: 1.058 ± 0.040 -> 1.045 ± 0.049 | Helped |
| Use LRS-RR instead of LR-RR | robust regression · YaleB | Fitting Err: 0.185 ± 0.006 -> 0.164 ± 0.006 | Helped |
Closest papers by meaning
- Adaptive Reduced Rank Regression (NeurIPS 2020 · similarity 0.89)
- Hardness and Algorithms for Robust and Sparse Optimization (ICML 2022 · similarity 0.89)
- Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension (ICLR 2022 · similarity 0.89)
- Robust Regression Revisited: Acceleration and Improved Estimation Rates (NeurIPS 2021 · similarity 0.88)
- Robust Sparse Regression with Non-Isotropic Designs (NeurIPS 2024 · similarity 0.87)
- Regularized least squares learning with heavy-tailed noise is minimax optimal (NeurIPS 2025 · similarity 0.85)
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.