{"id":"W3128801098","doi":"10.1109/focs46700.2020.00132","title":"Optimal anytime regret for two experts","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Regret; Computer science; Human–computer interaction; Artificial intelligence; Machine learning","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007686617,0.000112243,0.0002278969,0.000089982,0.0001284182,0.0001981033,0.0008300086,0.00004041672,0.002735469],"category_scores_gemma":[0.004769556,0.00007347172,0.0001163906,0.0005820478,0.00009229041,0.0004033479,0.000223795,0.00008370748,0.0009313341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000229118,"about_ca_system_score_gemma":0.00006879664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004189298,"about_ca_topic_score_gemma":0.000003262584,"domain_scores_codex":[0.9974564,0.00005750794,0.0003047032,0.0005713856,0.001241303,0.0003686726],"domain_scores_gemma":[0.9976295,0.001263735,0.00006190387,0.0003884088,0.000352761,0.0003036911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003523498,0.00005404469,0.0002390827,0.000004790179,0.00002135001,0.00004235057,0.001336799,0.01034476,0.004047628,0.001501584,0.8027712,0.1792841],"study_design_scores_gemma":[0.001388327,0.0003623596,0.00006844247,0.000002695082,0.000002412079,0.000007154783,0.001428056,0.3981081,0.01949193,0.005194571,0.573707,0.0002389954],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007062467,0.00009079501,0.9678625,0.01921581,0.0001448046,0.0004356108,0.00002431159,0.0001086623,0.005055083],"genre_scores_gemma":[0.5045461,0.000009624486,0.4335352,0.005182615,0.001412357,0.0001709701,0.00001411758,0.0000626765,0.05506626],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5343272,"threshold_uncertainty_score":0.9998466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.301288413499801,"score_gpt":0.5098735360741435,"score_spread":0.2085851225743425,"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."}}