{"id":"W2512885195","doi":"10.1109/isit.2016.7541444","title":"The rates of convergence of neural network estimates of hierarchical interaction regression models","year":2016,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Curse of dimensionality; Artificial neural network; Regression; Convergence (economics); Smoothness; Computer science; Regression analysis; Function (biology); Rate of convergence; Artificial intelligence; Class (philosophy); Mathematics; Machine learning; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02362086,0.002151385,0.00149735,0.002312691,0.000873535,0.001990051,0.003496299,0.00280245,0.002691566],"category_scores_gemma":[0.1303346,0.001575154,0.001733078,0.001184282,0.002637652,0.004876428,0.005302979,0.006086795,0.001099344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002539033,"about_ca_system_score_gemma":0.001713678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005532595,"about_ca_topic_score_gemma":0.004399654,"domain_scores_codex":[0.9918234,0.004946566,0.0004743584,0.001066635,0.001313982,0.0003750981],"domain_scores_gemma":[0.8923631,0.09331433,0.003907863,0.004728647,0.005054228,0.000631689],"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":[0.0004041483,0.0001164797,0.008143333,0.0006758909,0.0003706873,0.0002408091,0.0004033259,0.747171,0.004148664,0.1439287,0.00347927,0.09091766],"study_design_scores_gemma":[0.00001018384,0.00003226368,0.0007569807,0.00006463678,0.00002041045,0.00004911776,0.0000265023,0.9712186,0.001591094,0.02532264,0.0008779195,0.00002952316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01639184,0.00185601,0.9771631,0.0009811161,0.00009285871,0.00007264262,0.000143195,0.0005180482,0.00278119],"genre_scores_gemma":[0.491585,0.003649092,0.4903978,0.0007911542,0.0002953168,0.0008949413,0.001277549,0.001394981,0.009714246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02362086,"threshold_uncertainty_score":0.1249205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03229479305023773,"score_gpt":0.3030788595014925,"score_spread":0.2707840664512548,"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."}}