| title: Reproduction — Multi-task Linear Regression without Eigenvalue Lower Bounds | |
| emoji: 🛡️ | |
| colorFrom: purple | |
| colorTo: green | |
| sdk: static | |
| pinned: false | |
| tags: | |
| - icml2026-repro | |
| - paper-D5Ijcnz1L9 | |
| # Reproduction bundle | |
| Claim-native deterministic audit of all six registered claims for OpenReview | |
| `D5Ijcnz1L9` and arXiv `2605.17126v1`. The registered matrix-weighted MTLR | |
| estimator is executed directly on linear and logistic experiments at the | |
| paper's native synthetic dimensions. | |
| ```bash | |
| python3 -m pip install -r requirements.txt | |
| PYTHONDONTWRITEBYTECODE=1 PYTHONWARNINGS=error python3 reproduce.py | |
| PYTHONDONTWRITEBYTECODE=1 PYTHONWARNINGS=error python3 validate_evidence.py | |
| ``` | |
| Finite native-scale runs and exact covariance objects accompany the pinned | |
| high-probability theorems; they are not replacement universal proofs. | |