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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.
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