Update logbook: Reproduction: Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function
a74de38 verified | # Executive summary | |
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| We audited all 6 anchored theoretical claims with a standalone, self-contained NumPy/SciPy instrument. Outcome: **0 verified, 6 toy, 0 inconclusive.** All audits run on small controlled instances — no GPU, no training, on CPU only. Each claim page carries its pre-registered pass criterion, any protocol delta, the measured numbers, and the negative control where one was run. Claims whose criterion could not discriminate are labelled `toy` and say so on the page, rather than being reported as verified; where the anchored wording exceeds what the paper text supports, we say that plainly rather than overclaim. | |
| ## Scope & cost | |
| | Item | Value | | |
| | --- | --- | | |
| | GPU / compute | None. Pure NumPy/SciPy, CPU only | | |
| | Wall time | CPU-only; not separately timed | | |
| | Feasibility | High. Self-contained audit.py, deps NumPy/SciPy | | |
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| {"type": "figure", "id": "cell_cc28be3f96a9", "created_at": "2026-07-27T02:55:55+00:00", "title": "Reproduction poster (poster_embed.html)", "pinned": true, "pinned_at": "2026-07-27T02:55:55+00:00"} | |
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| ````html | |
| <p>Build a reproduction poster with <a href="https://github.com/Chenruishuo/posterly">Chenruishuo/posterly</a> and replace this cell with <code>poster_embed.html</code>.</p> | |
| ```` | |