{"id":"W3182947351","doi":"10.1007/s10994-021-05980-1","title":"Triply stochastic gradient method for large-scale nonlinear similar unlabeled classification","year":2021,"lang":"en","type":"article","venue":"Machine Learning","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; Government of Jiangsu Province; Six Talent Peaks Project in Jiangsu Province; National Natural Science Foundation of China","keywords":"Scalability; Classifier (UML); Computer science; Artificial intelligence; Generalization; Machine learning; Kernel (algebra); Stochastic gradient descent; Benchmark (surveying); Data point; Nonlinear system; Scale (ratio); Linear classifier; Algorithm; Mathematics; Artificial neural network","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":[0.002531276,0.0008280093,0.001977566,0.001293379,0.001037403,0.001232781,0.003045525,0.002042449,0.004519848],"category_scores_gemma":[0.00634543,0.0007777039,0.001292182,0.001380994,0.001302682,0.002046283,0.002311914,0.00247223,0.001502034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001204327,"about_ca_system_score_gemma":0.002267452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01005371,"about_ca_topic_score_gemma":0.01085402,"domain_scores_codex":[0.9989232,0.000411039,0.00005606647,0.0002117567,0.0003020485,0.00009579908],"domain_scores_gemma":[0.997619,0.00114782,0.0001464165,0.0003564596,0.0005594093,0.000170857],"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":[0.0004088243,0.0003715537,0.001456939,0.0003018827,0.0002322644,0.0001910629,0.0001334672,0.5414463,0.00651142,0.06925856,0.01592205,0.3637657],"study_design_scores_gemma":[0.000006890457,0.00001051305,0.00004912992,0.000002233289,0.000004184446,0.0000105627,0.000003048546,0.994799,0.0002333193,0.004546736,0.0003303556,0.000003887006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004771209,0.0001670932,0.993695,0.0001539191,0.00004241515,0.00005524556,0.00006449848,0.0005683284,0.0004823762],"genre_scores_gemma":[0.242493,0.0003552119,0.7459824,0.0004117452,0.0002367749,0.0004886705,0.001209133,0.0005246867,0.008298302],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01005371,"threshold_uncertainty_score":0.01999032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02435636714648145,"score_gpt":0.3079578563482156,"score_spread":0.2836014892017342,"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."}}