{"id":"W4400149513","doi":"10.2139/ssrn.4880211","title":"Transfer Learning in Bayesian Optimization: An Accelerated Search Strategy","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Bayesian optimization; Bayesian probability; Computer science; Transfer of learning; 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":[0.005360626,0.001353288,0.002172398,0.00158218,0.0009013549,0.001593671,0.002919838,0.004438695,0.008549697],"category_scores_gemma":[0.02345156,0.001189169,0.001550155,0.001935409,0.002034829,0.003754887,0.004373186,0.003854051,0.001783241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001212005,"about_ca_system_score_gemma":0.001856432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002761304,"about_ca_topic_score_gemma":0.002298803,"domain_scores_codex":[0.9981134,0.001177644,0.00006353149,0.0001367342,0.0004191123,0.00008962153],"domain_scores_gemma":[0.9939263,0.00469075,0.0001933061,0.000422397,0.000578801,0.0001884173],"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":[0.0002620451,0.0002354683,0.0005349902,0.0003290702,0.0001697348,0.0001611312,0.0001776411,0.5045975,0.001324742,0.3765325,0.008589476,0.1070857],"study_design_scores_gemma":[0.00004484479,0.00003286502,0.00005594214,0.00001758453,0.00001710844,0.00002436463,0.000007517123,0.9438577,0.0001539581,0.054862,0.0009175822,0.000008532146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006131828,0.0005214403,0.9867076,0.0006758946,0.0001563238,0.00006881867,0.00002640323,0.0001693936,0.005542428],"genre_scores_gemma":[0.2439659,0.001262486,0.7341033,0.000788363,0.0008831812,0.001056439,0.0001844527,0.0005599783,0.01719589],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008549697,"threshold_uncertainty_score":0.02860159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01897565341112499,"score_gpt":0.2933797084077899,"score_spread":0.2744040549966649,"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."}}