{"id":"W4416932885","doi":"10.48550/arxiv.2512.00170","title":"We Still Don't Understand High-Dimensional Bayesian Optimization","year":2025,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Research England; Natural Sciences and Engineering Research Council of Canada; National Science Foundation; Government of Canada; Canadian Institute for Advanced Research","keywords":"Curse of dimensionality; Bayesian optimization; Bayesian probability; Exploit; Gaussian process; Locality; Computation; Optimization problem","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006760415,0.001049813,0.001857162,0.0009486213,0.0009972739,0.004412949,0.003001168,0.004526364,0.007815897],"category_scores_gemma":[0.02853931,0.001066569,0.0009642843,0.001052561,0.008278399,0.01776361,0.003173004,0.01560196,0.004727238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001541114,"about_ca_system_score_gemma":0.001381682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003269149,"about_ca_topic_score_gemma":0.002785864,"domain_scores_codex":[0.9974935,0.0008978964,0.0001095177,0.0006120252,0.0007614231,0.0001257117],"domain_scores_gemma":[0.9887861,0.007279307,0.0006017832,0.001822525,0.001084351,0.0004259825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002381911,0.00004168014,0.0008438717,0.00034691,0.00009327388,0.00004576158,0.0002533992,0.01610531,0.0004344522,0.903528,0.02474019,0.05354331],"study_design_scores_gemma":[0.00001276097,0.000017472,0.0002432902,0.0001088058,0.000008927534,0.00005093146,0.00007634061,0.04390081,0.00022406,0.9293218,0.02600367,0.00003106183],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.002461009,0.004510417,0.9330601,0.04787179,0.0006650258,0.00002524434,0.0002817855,0.0004964575,0.01062825],"genre_scores_gemma":[0.2196419,0.01831148,0.7037826,0.02717112,0.005226782,0.000432922,0.0006843115,0.001432062,0.0233168],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.007815897,"threshold_uncertainty_score":0.03575295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0456381393242947,"score_gpt":0.1854230976882942,"score_spread":0.1397849583639995,"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."}}