Эксперимент: Anytime Primal-Dual Neural Robustness Radius (#1131)

{ "worked": false, "confidence": 9, "verdict": "Built a generic reduced primal-dual LP hierarchy with explicit full-space residual and coverage checks, plus deterministic toy verification and repeated timing benchmark. The claimed certificate behavior was observed: all intervals covered the full optimum, lower bounds increased, upper bounds and widths were nonincreasing, and the final level attained strong duality. However, the MVP did not demonstrate the promised speedup: median cumulative hierarchy time was 0.0742 s versus 0.00692 s for a full solve, and the 2% width target was reached only at the final level; moreover, the dual hierarchy was oracle-seeded with the full dual optimizer.", "metrics": { "baseline": "Full LP: median 0.00692 s across 5 trials; exact optimum solved directly.", "idea": "Oracle-seeded reduced hierarchy: median 0.0742 s for all levels, 10.7x slower; 2% relative-width stopping occurred at level 11/11 in every trial. Toy checks showed 100% coverage and monotonicity across tested levels." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 run_experiment.py && /home/maxwelhelp/main/bin/python3 benchmark.py", "files": [ "anytime_pd.py", "run_experiment.py", "benchmark.py" ], "limitations": "No ReLU MLP/CNN relaxation was built, no MNIST experiment was run, and no fair non-oracle dual-space initialization or warm-started solver comparison was implemented. The benchmark is small and uses SciPy HiGHS, so it does not establish neural verification performance." }