{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00461566,0.001409463,0.001754027,0.00058139,0.00070845,0.001532405,0.002196972,0.00242964,0.003180466],"category_scores_gemma":[0.01828452,0.0005908025,0.0009970455,0.0007272093,0.001564221,0.00276514,0.001966101,0.003030139,0.0006478041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001885586,"about_ca_system_score_gemma":0.001917692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001919091,"about_ca_topic_score_gemma":0.00159955,"domain_scores_codex":[0.9972916,0.001100542,0.00009079065,0.0006329604,0.0004978838,0.0003861472],"domain_scores_gemma":[0.9927742,0.005280335,0.0005725521,0.0006517661,0.0004123087,0.0003086947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00078992,0.0002678345,0.001171259,0.0002617942,0.0001399571,0.0001295351,0.0002596503,0.6911727,0.003262412,0.2065521,0.007257491,0.08873535],"study_design_scores_gemma":[0.00006059072,0.00007736549,0.000198504,0.00002186856,0.00001669392,0.00003123277,0.00001465233,0.9203991,0.0009826109,0.07735852,0.0008249372,0.00001391736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04128285,0.0004822001,0.9495627,0.00129054,0.0001091673,0.00009122331,0.0001295628,0.0003476547,0.006704019],"genre_scores_gemma":[0.7484336,0.0004580414,0.2344805,0.0006657765,0.0003158511,0.0004183365,0.0003281736,0.0001964028,0.01470344],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00461566,"threshold_uncertainty_score":0.02441025,"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."}}