{"id":"W2798463223","doi":"","title":"Statistical Sparse Online Regression: A Diffusion Approximation Perspective.","year":2018,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence and Statistics","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Perspective (graphical); Diffusion; Computer science; Regression; Regression analysis; Statistics; Artificial intelligence; Machine learning; Econometrics; Mathematics; Physics","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":[0.003796307,0.0009091569,0.001399544,0.001187383,0.000391348,0.001425495,0.002460636,0.002112782,0.002341639],"category_scores_gemma":[0.02940568,0.0008115747,0.0006189216,0.001970186,0.001550048,0.003963381,0.001771451,0.003408476,0.0006584546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003766,"about_ca_system_score_gemma":0.001028122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005705653,"about_ca_topic_score_gemma":0.00561953,"domain_scores_codex":[0.9987715,0.0006315145,0.00005741672,0.0001539605,0.0002890669,0.00009648671],"domain_scores_gemma":[0.9863452,0.0104261,0.000734345,0.001044333,0.001146883,0.0003032812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001433491,0.0001294014,0.0022051,0.0002818325,0.0001942117,0.0001942163,0.0001676985,0.4419657,0.002163909,0.4380561,0.01409939,0.1003991],"study_design_scores_gemma":[0.000006914522,0.00001026542,0.0001133137,0.0000123016,0.0000100639,0.00002655407,0.000009181357,0.9443605,0.0002404775,0.05410525,0.001099065,0.000005999826],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006314,0.001623016,0.9876842,0.001952278,0.0001261021,0.00002336183,0.0001048003,0.000227359,0.001944853],"genre_scores_gemma":[0.5775858,0.00641144,0.3932167,0.001096872,0.001459347,0.0002511865,0.0009184086,0.0004471593,0.01861313],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005705653,"threshold_uncertainty_score":0.02007705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1049720817424107,"score_gpt":0.3812492784967594,"score_spread":0.2762771967543487,"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."}}