{"id":"W4211215680","doi":"10.1017/9781108571401.036","title":"The Relation between Adversarial and Stochastic Linear Bandits","year":2020,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Relation (database); Adversarial system; Content (measure theory); Computer science; Mathematical optimization; Theoretical computer science; Artificial intelligence; Mathematics; Data mining","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"],"consensus_categories":[],"category_scores_codex":[0.0007029336,0.00033301,0.0004842161,0.0002286733,0.0008266654,0.0002030877,0.001155245,0.0003707033,0.000006791918],"category_scores_gemma":[0.0008271929,0.0002673348,0.0001782606,0.00003708561,0.0007167333,0.0002193001,0.001068103,0.0009650439,0.0001011529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001639212,"about_ca_system_score_gemma":0.0001897377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002356045,"about_ca_topic_score_gemma":0.000002714968,"domain_scores_codex":[0.9966741,0.0001459185,0.0004018819,0.0008462433,0.001600897,0.0003310263],"domain_scores_gemma":[0.9953466,0.002774593,0.0003974335,0.0007078871,0.0004377866,0.0003356829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001017921,0.000007920764,0.00001831316,0.00003319772,0.0004488932,0.000424785,0.0002965831,0.0006146815,0.00001750692,0.8838364,0.05671644,0.05656738],"study_design_scores_gemma":[0.0008576897,0.000108358,0.0002317889,0.00004637922,0.0001236939,0.00000654025,0.00007343036,0.003384623,0.00002050082,0.0007678437,0.9940234,0.0003557162],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0000650313,0.0002475826,0.09831295,0.0002509689,0.0005037662,0.0008819871,0.0006031975,0.0001081231,0.8990264],"genre_scores_gemma":[0.005614539,0.00005443092,0.0001579828,0.00001933924,0.0007232447,7.025158e-7,0.00003780607,0.00004023734,0.9933517],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.937307,"threshold_uncertainty_score":0.9999779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09798280793259397,"score_gpt":0.3136995318673979,"score_spread":0.215716723934804,"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."}}