# Стенд-проверка (stage-2) · промт оператора:

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 10,
  "verdict": "Built the Inexact High-Order Moreau DC optimizer as an optimizer-only modification of the benchmark's shared mlp_tiny architecture on the structurally matched tabular Friedman#1 regression track. The mechanism signature was confirmed quantitatively: the observed mean ||G_HOME||/||raw DC gradient|| ratio was 0.255, indicating update attenuation. However, the idea had test MSE 104.757 versus baseline 11.692, with paired permutation p=0.0081 in favor of the baseline, so the promised benchmark win was not observed.",
  "metrics": {
    "baseline": "AdamW sweep best lr=0.006, weight_decay=0.0001; 8-seed test MSE mean=11.6917993, std=1.2449598",
    "idea": "HOME-DC best finite sweep p=2, gamma=0.03, lr=0.006; 8-seed test MSE mean=104.7572689, std=5.9293015",
    "paired_delta": "idea-baseline = +93.0654696 MSE; permutation p=0.0081; verdict idea worse (significant)",
    "mechanism": "Observed mean update-norm ratio ||G_HOME||/||raw DC gradient||=0.2545768, median=0.2223473 over 80 minibatch measurements; confirmed=true"
  },
  "bench_report": {
    "bench_version": 1,
    "track": "tabular",
    "model": "mlp_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.006,
        "wd": 0.0001
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001,
            "wd": 0.0
          },
          "mean": 52.02932357788086
        },
        {
          "cfg": {
            "lr": 0.001,
            "wd": 0.0001
          },
          "mean": 51.98645782470703
        },
        {
          "cfg": {
            "lr": 0.003,
            "wd": 0.0
          },
          "mean": 14.625996589660645
        },
        {
          "cfg": {
            "lr": 0.003,
            "wd": 0.0001
          },
          "mean": 14.602366924285889
        },
        {
          "cfg": {
            "lr": 0.006,
            "wd": 0.0
          },
          "mean": 11.602271318435669
        },
        {
          "cfg": {
            "lr": 0.006,
            "wd": 0.0001
          },
          "mean": 11.320476055145264
        }
      ],
      "full": {
        "mean": 11.691799283027649,
        "std": 1.2449598187957995,
        "per_seed": [
          11.544059753417969,
          12.460237503051758,
          10.659576416015625,
          10.618030548095703,
          9.606558799743652,
          12.408422470092773,
          12.555534362792969,
          13.681974411010742
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 104.75726890563965,
      "std": 5.929301472950579,
      "per_seed": [
        102.7054443359375,
        102.88192749023438,
        106.44611358642578,
        95.48319244384766,
        116.45075988769531,
        102.46852111816406,
        101.3128662109375,
        110.309326171875
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 93.065469622612,
      "idea_wins": 0,
      "n_pairs": 8,
      "per_seed_diffs": [
        91.16138458251953,
        90.42168998718262,
        95.78653717041016,
        84.86516189575195,
        106.84420108795166,
        90.06009864807129,
        88.75733184814453,
        96.62735176086426
      ],
      "p_value": 0.0081,
      "mde": 5.612624544400254,
      "mde_rel_pct": 48.00479728169638,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "idea_sweep": [
      {
        "cfg": {
          "lr": 0.006,
          "p": 2,
          "gamma": 0.03
        },
        "mean": 101.87916946411133,
        "n": 4
      },
      {
        "cfg": {
          "lr": 0.006,
          "p": 2,
          "gamma": 0.1
        },
        "mean": 157.33378219604492,
        "n": 4
      },
      {
        "cfg": {
          "lr": 0.006,
          "p": 2,
          "gamma": 0.3
        },
        "mean": 173.4729461669922,
        "n": 4
      },
      {
        "cfg": {
          "lr": 0.001,
          "p": 4,
          "gamma": 0.1
        },
        "mean": 233.65539169311523,
        "n": 4
      },
      {
        "cfg": {
          "lr": 0.003,
          "p": 4,
          "gamma": 0.1
        },
        "mean": 227.60537338256836,
        "n": 4
      },
      {
        "cfg": {
          "lr": 0.006,
          "p": 4,
          "gamma": 0.1
        },
        "mean": 206.5521469116211,
        "n": 4
      }
    ],
    "selection_cfg": {
      "lr": 0.006,
      "p": 2,
      "gamma": 0.03
    },
    "equal_budget": {
      "epochs": 16,
      "batch": 128
    },
    "mechanism_signature": {
      "quantity": "||G_HOME|| / ||raw DC gradient|| on minibatches from trained benchmark runs",
      "predicted": "smoothing should attenuate updates",
      "observed_mean_ratio": 0.25457684118531804,
      "observed_median_ratio": 0.22234734467118233,
      "n": 80,
      "confirmed": true
    }
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py",
  "files": [
    "bench_experiment.py",
    "bench_report.json"
  ],
  "limitations": "Only the structurally matched tabular Friedman#1 track and mlp_tiny architecture were tested; vision, sequence, and dynamics tracks were not applicable to this optimizer/regularizer idea. The implementation used a fixed three-step inner solve, a fixed local curvature coefficient, and a small benchmark budget; no larger models, adaptive residual stopping, exact proximal solves, or broader regularizer/DC decompositions were tested. The mechanism signature confirms update attenuation, not improved optimization or generalization.",
  "system_verdict": "partial",
  "practical_verdict": "harms",
  "mechanism_ok": 1,
  "system_judged": true
}