{"id":"W4322707172","doi":"10.1109/tit.2023.3250099","title":"Martingale Methods for Sequential Estimation of Convex Functionals and Divergences","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Mathematics; Regular polygon; Martingale (probability theory); Applied mathematics; Convex function; Kullback–Leibler divergence; Logarithm; Probability measure; Combinatorics; Discrete mathematics; Mathematical optimization; Statistics; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01158974,0.002616487,0.002216807,0.003048826,0.0006346884,0.002444827,0.003349045,0.001808532,0.0045892],"category_scores_gemma":[0.04469908,0.001374534,0.002445936,0.001859314,0.003367483,0.004888594,0.00466253,0.006278111,0.0009747843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002123649,"about_ca_system_score_gemma":0.00254422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001971501,"about_ca_topic_score_gemma":0.001643752,"domain_scores_codex":[0.9952166,0.002171808,0.0002906085,0.0009016469,0.001116884,0.0003023776],"domain_scores_gemma":[0.9718201,0.02196492,0.001714404,0.002212225,0.001703961,0.0005844994],"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":[0.0001100074,0.00009817891,0.001084013,0.0002640068,0.0001634134,0.0001494022,0.0001682413,0.2801159,0.002835194,0.6590673,0.001418522,0.05452565],"study_design_scores_gemma":[0.00001204376,0.00006055081,0.0001593076,0.0000370771,0.00001783664,0.00004012976,0.000009950542,0.8263358,0.001551074,0.1701631,0.001588085,0.00002509796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006714453,0.00007476975,0.9987987,0.00005107157,0.00001361538,0.00001391864,0.00002343783,0.00006175311,0.0002913315],"genre_scores_gemma":[0.1702168,0.0009901901,0.8212227,0.0003437322,0.0003548895,0.0006806061,0.000564987,0.0004542063,0.005171758],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01158974,"threshold_uncertainty_score":0.06129313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07514884128663901,"score_gpt":0.4022217221927577,"score_spread":0.3270728809061187,"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."}}