Upload results/benchmark_200K_a10g_2026-05-05.json
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results/benchmark_200K_a10g_2026-05-05.json
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{
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"config": {
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"max_rows": 200000,
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"budget": 10000.0,
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"T": 10000,
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"vpc": 50.0,
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"k": 0.8,
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"n_runs": 5,
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"seed": 42,
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"ctr_test_auc": 0.6947,
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"algorithms": ["DualOGD", "TwoSidedDual", "ValueShading", "RLB", "Linear", "Threshold"],
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"run_date": "2026-05-05",
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"hardware": "a10g-small",
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"data_size": "200K rows (Criteo_x4)",
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"auction_type": "first-price",
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"market_price": "log-normal conditioned on pCTR features"
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},
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"aggregated": {
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"TwoSidedDual": {
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"clicks_mean": 284.6,
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"clicks_std": 8.3,
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"cpc_mean": 33.41,
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"cpc_std": 0.86,
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"budget_used_mean": 0.950,
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"budget_used_std": 0.005,
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"win_rate_mean": 0.076,
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"win_rate_std": 0.002
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},
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"ValueShading": {
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"clicks_mean": 257.8,
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"clicks_std": 7.4,
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"cpc_mean": 38.82,
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"cpc_std": 1.14,
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"budget_used_mean": 1.0,
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"budget_used_std": 0.0,
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"win_rate_mean": 0.082,
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"win_rate_std": 0.002
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},
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"DualOGD": {
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"clicks_mean": 248.0,
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"clicks_std": 9.4,
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"cpc_mean": 31.18,
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"cpc_std": 1.13,
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"budget_used_mean": 0.773,
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"budget_used_std": 0.027,
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"win_rate_mean": 0.066,
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"win_rate_std": 0.002
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},
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"RLB": {
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"clicks_mean": 135.8,
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"clicks_std": 13.3,
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"cpc_mean": 74.34,
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"cpc_std": 7.16,
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"budget_used_mean": 1.0,
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"budget_used_std": 0.0,
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"win_rate_mean": 0.042,
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"win_rate_std": 0.004
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},
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"Threshold": {
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"clicks_mean": 71.0,
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"clicks_std": 4.1,
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"cpc_mean": 70.36,
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"cpc_std": 3.96,
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"budget_used_mean": 0.0,
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"budget_used_std": 0.0,
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"win_rate_mean": 0.017,
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"win_rate_std": 0.001
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},
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"Linear": {
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"clicks_mean": 63.6,
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"clicks_std": 6.0,
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"cpc_mean": 79.20,
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"cpc_std": 6.17,
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"budget_used_mean": 0.0,
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"budget_used_std": 0.0,
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"win_rate_mean": 0.020,
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"win_rate_std": 0.003
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}
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},
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"notes": {
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"data_note": "Linear and Threshold show 0% budget used because they were configured with infinite internal budget. They actually spent ~5000 each. The set_budget call is being fixed in a follow-up.",
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"ctr_model": "LogisticRegression (max_iter=500, C=0.1), AUC=0.6947",
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"two_sided_dual_advantage": "The TwoSidedDual beats DualOGD by spending 95% vs 77% of budget, converting 15% more clicks. The floor multiplier ν prevents the dual from becoming too conservative.",
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"rl_performance": "RLB underperforms because it needs more data to learn its Q-table. With only 10K auctions per run, the tabular approach hasn't covered the state space.",
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"citation": "All algorithms documented in RESEARCH_RESOURCES.md. Primary paper: Wang et al. 2023, arXiv:2304.13477"
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}
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}
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