{"id":"W1589610332","doi":"10.1023/a:1008347431468","title":"Central Limit Theorems for Stochastic Optimization Algorithms Using Infinitesimal Perturbation Analysis","year":2000,"lang":"en","type":"article","venue":"Discrete Event Dynamic Systems","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Mathematics; Queue; Mathematical optimization; Constant (computer programming); Convergence (economics); Context (archaeology); Asymptotically optimal algorithm; Rate of convergence; Perturbation (astronomy); Applied mathematics; Computer science; Key (lock)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01479887,0.003036361,0.002933809,0.00294775,0.00126983,0.003618699,0.003478694,0.002702317,0.004358736],"category_scores_gemma":[0.03972426,0.001452502,0.002212367,0.002686304,0.005830094,0.006681202,0.005507505,0.007027906,0.0007388175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002623911,"about_ca_system_score_gemma":0.003402561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00293918,"about_ca_topic_score_gemma":0.002498332,"domain_scores_codex":[0.9961039,0.002281657,0.0001706766,0.0003765117,0.0008800344,0.0001872783],"domain_scores_gemma":[0.9734427,0.02133719,0.00115058,0.0008923959,0.002500885,0.0006763645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007089914,0.00007202924,0.0002254109,0.0002081782,0.0001238573,0.00007746647,0.0001213039,0.1525551,0.0009869644,0.8324187,0.001744591,0.01139538],"study_design_scores_gemma":[0.00001761315,0.0000244633,0.00008914874,0.00003006571,0.00002320108,0.00002324736,0.00001453926,0.6940515,0.0004087995,0.3043833,0.0009140956,0.00002000023],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002641952,0.0006058415,0.9930317,0.0004160585,0.0001104275,0.0000303017,0.00003435919,0.0000740502,0.003055312],"genre_scores_gemma":[0.431301,0.006179421,0.5288752,0.00145449,0.001242949,0.001822955,0.0004600897,0.001293191,0.02737062],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01479887,"threshold_uncertainty_score":0.07826489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01317568230108289,"score_gpt":0.268686991798461,"score_spread":0.2555113094973781,"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."}}