{"id":"W2952938032","doi":"10.48550/arxiv.1110.6755","title":"PAC-Bayes-Bernstein Inequality for Martingales and its Application to\\n Multiarmed Bandits","year":2011,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Bayes' theorem; Computer science; Inequality; Mathematical optimization; Interdependence; Artificial intelligence; Mathematics; Bayesian probability","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004807758,0.0009075592,0.001287516,0.001144102,0.0009570891,0.0003026016,0.002578622,0.0008109635,0.0003645751],"category_scores_gemma":[0.004507781,0.0009572697,0.000473974,0.002052642,0.0006373525,0.0009528263,0.003434549,0.001027137,0.0007915255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005111019,"about_ca_system_score_gemma":0.0004670676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002954814,"about_ca_topic_score_gemma":0.0004232664,"domain_scores_codex":[0.9914093,0.0008484653,0.001297548,0.004310952,0.0007564072,0.001377353],"domain_scores_gemma":[0.9900946,0.003040771,0.001229089,0.002229677,0.00217856,0.001227324],"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":[0.01512092,0.003947885,0.06876649,0.00301953,0.001763427,0.0006540622,0.01352258,0.4732819,0.01094977,0.1216179,0.002445239,0.2849104],"study_design_scores_gemma":[0.004117868,0.0006903465,0.02127649,0.0003192801,0.0002674929,0.00001035136,0.001747844,0.7933979,0.0082725,0.158166,0.00949316,0.002240725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3624038,0.0001539982,0.6322049,0.0001991052,0.000453447,0.00372721,0.0003952426,0.00009723548,0.0003650946],"genre_scores_gemma":[0.9909636,0.0004646011,0.002165799,0.00008428859,0.000270292,0.00005743388,0.00005926019,0.00007770352,0.005857027],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6300391,"threshold_uncertainty_score":0.9999865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.278027064030556,"score_gpt":0.3265386299181593,"score_spread":0.04851156588760325,"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."}}