{"id":"W6979268663","doi":"","title":"Minimax Rate-Optimal Algorithms for High-Dimensional Stochastic Linear Bandits","year":2025,"lang":"en","type":"article","venue":"ArXiv.org","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Minimax; Regret; Estimator; Lasso (programming language); Logarithm; Upper and lower bounds; Thresholding; Dimension (graph theory); Least-squares function approximation","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":["insufficient_payload"],"category_scores_codex":[0.00243533,0.0003347507,0.0005775904,0.0006194395,0.0005313868,0.0001421914,0.001136805,0.0001945054,0.001338145],"category_scores_gemma":[0.007291218,0.0002610782,0.0002197523,0.00145927,0.0003357237,0.0004700301,0.0004614846,0.0003962184,0.001710609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001266109,"about_ca_system_score_gemma":0.0004258702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000281331,"about_ca_topic_score_gemma":0.00001542223,"domain_scores_codex":[0.995531,0.0001991855,0.0008885526,0.001163985,0.00136939,0.0008479314],"domain_scores_gemma":[0.9925481,0.004953486,0.0002046303,0.0008956954,0.001145066,0.000253012],"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":[0.005164871,0.002394985,0.04587228,0.0001689893,0.001067406,0.0004467395,0.001064523,0.3962665,0.02121512,0.005162393,0.2670965,0.2540798],"study_design_scores_gemma":[0.01272179,0.001714434,0.2434456,0.0002350842,0.0001715636,0.00004032817,0.0008817643,0.5884984,0.04023966,0.05128963,0.05867806,0.002083699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4500089,0.0002311526,0.5453328,0.001916546,0.001469077,0.000705398,0.0001301227,0.00009606559,0.0001098629],"genre_scores_gemma":[0.9459313,0.000007450187,0.02144772,0.0006689452,0.0005949168,0.0002312628,0.00006576945,0.00004979561,0.03100289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5238851,"threshold_uncertainty_score":0.9999841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1399943811085759,"score_gpt":0.4363972147109591,"score_spread":0.2964028336023832,"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."}}