{"id":"W2074149593","doi":"10.1007/s10589-007-9159-0","title":"Improved convergence order for augmented penalty algorithms","year":2008,"lang":"en","type":"article","venue":"Computational Optimization and Applications","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Mathematics; Augmented Lagrangian method; Convergence (economics); Multiplier (economics); Quadratic equation; Order (exchange); Penalty method; Compact convergence; Mathematical optimization; Normal convergence; Applied mathematics; Convergence tests; Algorithm; Rate of convergence; Computer science; Key (lock)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001432683,0.000160594,0.0001807196,0.0001307484,0.0006259313,0.00003526582,0.0001439431,0.00006996337,0.0001906439],"category_scores_gemma":[0.0002068481,0.0001673672,0.00004570515,0.0005483465,0.0001704895,0.0002019579,0.00005455607,0.00009327381,0.000008753356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005161752,"about_ca_system_score_gemma":0.000147807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002633991,"about_ca_topic_score_gemma":9.584088e-7,"domain_scores_codex":[0.9987603,0.00003302031,0.0003798788,0.0003712555,0.0002421155,0.0002134092],"domain_scores_gemma":[0.9979121,0.0005177266,0.0001628024,0.0001845022,0.001077829,0.000145005],"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":[0.00001789319,0.0001721074,0.00004455296,0.00003939636,0.00003251486,4.105061e-7,0.0001083904,0.9345822,0.00002154147,0.06127711,0.001162907,0.002540948],"study_design_scores_gemma":[0.0009883177,0.00003272204,0.00005961518,0.00000541196,0.00001358942,0.00002332664,0.00004710492,0.9748398,0.00004780329,0.02017405,0.003584462,0.0001838132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00009168485,0.00005911543,0.9970656,0.0007126335,0.00003770093,0.001489491,0.00008520923,0.0001615125,0.0002970766],"genre_scores_gemma":[0.006193603,0.0001356178,0.9901092,0.000224346,0.0001022669,0.001168647,0.0005214767,0.0000390978,0.001505743],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04110307,"threshold_uncertainty_score":0.6825038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06084120631137142,"score_gpt":0.363099416639977,"score_spread":0.3022582103286056,"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."}}