SabaPivot/repro-batch20-c-audits / batch_results.json
SabaPivot's picture
download
raw
2.81 kB
{
"scope": "Independent lightweight numerical audits; not full benchmark replications or proof replacements.",
"optimal_design_mnl": {
"candidate_assortments": 92,
"vectorized_lmo_matches_bruteforce": true,
"logdet_initial": -3.090597986040936,
"logdet_final": -1.7823579291243272,
"logdet_gain": 1.3082400569166086,
"active_support": 5
},
"wasserstein_noise": {
"W1_loglog_slope": 1.0080943932202417,
"W2_loglog_slope": 0.5041625838491619,
"expected_mechanism_slopes": {
"W1": 1.0,
"W2": 0.5
},
"sigma_grid": [
2e-05,
3.698622388594646e-05,
6.839903786706794e-05,
0.0001264911064067352,
0.0002339214190570292,
0.0004325934988480796,
0.0008
],
"mean_W1": [
0.0011269742688427284,
0.002042236813882843,
0.003985322902105246,
0.007360052884819259,
0.013328342199604852,
0.024848910099849228,
0.046338389323970934
],
"mean_W2": [
0.03277867506463554,
0.04424370160767486,
0.06180436655620729,
0.08393480186436757,
0.11321713854550827,
0.15456198892436532,
0.20999700567202614
]
},
"riemannian_dueling": {
"dimension": 20,
"cosine_to_normalized_gradient": {
"200": 0.9396993363983441,
"2000": 0.9932077226110302,
"20000": 0.9989399432766883
},
"tangent_violation": 1.661214055315058e-16
},
"sinkhorn_diffusion": {
"iterations_to_row_error_below_0.1pct": 7,
"final_row_error": 4.0967229608668276e-14,
"symmetry_error": 2.7755575615628914e-17,
"minimum_entry": 3.712683991149634e-10,
"eigenvalue_min": -1.682513188523743e-16,
"eigenvalue_max": 0.9999999999999993
},
"semi_knockoffs": {
"target_fdr": 0.1,
"empirical_fdr": 0.09587345564793033,
"mean_power": 0.9777875,
"replicates": 1000,
"scope": "sign-flip/knockoff+ calibration proxy; not the released Semi-knockoffs implementation"
},
"sgmcmc_covariance": {
"step_size_error_loglog_slope": 1.0298834996115878,
"rows": [
{
"lambda": 0.005,
"proxy_relative_error": 0.00175967823026677,
"mc_to_exact_error": 0.07629438279863397
},
{
"lambda": 0.01,
"proxy_relative_error": 0.0035389282103134357,
"mc_to_exact_error": 0.047974964037807
},
{
"lambda": 0.02,
"proxy_relative_error": 0.007157464212678843,
"mc_to_exact_error": 0.031040999131076347
},
{
"lambda": 0.04,
"proxy_relative_error": 0.014644351464435263,
"mc_to_exact_error": 0.062354210035422034
},
{
"lambda": 0.08,
"proxy_relative_error": 0.03070175438596485,
"mc_to_exact_error": 0.01728348705581277
}
]
}
}

Xet Storage Details

Size:
2.81 kB
·
Xet hash:
0d39beeacfad31b0588c915d091a1d1225f5394e2f60252d4b2302f9176dca7d

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.