{"id":"W3105596848","doi":"10.1007/s10107-022-01787-7","title":"Constrained stochastic blackbox optimization using a progressive barrier and probabilistic estimates","year":2022,"lang":"en","type":"article","venue":"Mathematical Programming","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Probabilistic logic; Mathematical optimization; Martingale (probability theory); Mathematics; Constraint (computer-aided design); Function (biology); Constrained optimization; Probability distribution; Convergence (economics); Computer science; Algorithm; Applied mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004813306,0.001727538,0.002741231,0.001176456,0.0006421146,0.002293592,0.002505914,0.002735675,0.004873287],"category_scores_gemma":[0.01345864,0.00132237,0.001233512,0.001133935,0.002352455,0.004129683,0.003911632,0.003266733,0.0006052295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001334173,"about_ca_system_score_gemma":0.001968091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002160051,"about_ca_topic_score_gemma":0.001674148,"domain_scores_codex":[0.9987286,0.0006997424,0.000047069,0.0001784206,0.0002626595,0.00008353327],"domain_scores_gemma":[0.9945129,0.004238857,0.0003554192,0.0002646339,0.0003689755,0.0002592503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001196875,0.00007335652,0.0001493661,0.000174615,0.00006484985,0.00007360712,0.0000460351,0.6861567,0.001356831,0.3000727,0.001539842,0.01017233],"study_design_scores_gemma":[0.000007137368,0.00001145571,0.00001672934,0.000009935616,0.000004792707,0.000006294435,0.000002082257,0.9757335,0.0001940331,0.02373352,0.0002754554,0.000005026724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0040289,0.0002285502,0.9932653,0.0002361882,0.00005467375,0.0000234168,0.00002700617,0.00007809174,0.002057938],"genre_scores_gemma":[0.4360828,0.0008825553,0.5404431,0.0003584778,0.0002085109,0.0004754445,0.00016871,0.0005693654,0.02081101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004873287,"threshold_uncertainty_score":0.02545547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02158985536168916,"score_gpt":0.26737849543904,"score_spread":0.2457886400773508,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}