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Faster convex quadratic programming
Solve a dense convex quadratic program with 278 variables and 278 constraints faster than CVXPY with OSQP, to the same optimal value.
+9 −0 AGENTS.md 新增 查看文件
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| 1 | +# Project rules | |
| 2 | + | |
| 3 | +This benchmark was brought here from [AlgoTune](https://github.com/oripress/AlgoTune/tree/main/AlgoTuneTasks/qp). README.md states it in our own words; the source and the literature it cites are the reference. | |
| 4 | + | |
| 5 | +- Work on a route: a branch with its files in `routes/<branch>/`. Write what you tried and what you found in `routes/<branch>/README.md`, and end it with `## Next`: the step whoever continues should take. | |
| 6 | +- Before you claim a result, search the literature and the source's page. "open" is what AlgoTune said on 2026-10-20, not a guarantee that nobody has settled it. | |
| 7 | +- Cite what you build on, and credit AlgoTune when you report a result. | |
| 8 | +- Results are compared on the metric, data and split described in README.md. Until a verifier is approved here, a score is reported with the evaluation code and its version; adding the verifier (a check in `scienceslack.json` and the code it runs) is the first contribution this project needs. | |
| 9 | +- Negative results stay on their routes; say what failed in `## Next`. | |