{"id":"W2021175697","doi":"10.1080/00036811.2010.541447","title":"A proximal augmented Lagrangian method for equilibrium problems","year":2011,"lang":"en","type":"article","venue":"Applicable Analysis","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Mathematics; Augmented Lagrangian method; Intersection (aeronautics); Sequence (biology); Banach space; Convergence (economics); Projection method; Applied mathematics; Projection (relational algebra); Solution set; Lagrangian; Set (abstract data type); Mathematical optimization; Dykstra's projection algorithm; Mathematical analysis; Algorithm; Computer science","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":[0.001276605,0.0008353486,0.0009864813,0.0008652882,0.0005458128,0.0009383525,0.001303192,0.001381502,0.003306251],"category_scores_gemma":[0.00149054,0.0004365197,0.0008809772,0.0004751574,0.00129884,0.001172197,0.002111774,0.001674563,0.0009241482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005332073,"about_ca_system_score_gemma":0.001405961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001465476,"about_ca_topic_score_gemma":0.001440391,"domain_scores_codex":[0.9994996,0.0002015093,0.00001685057,0.00006402264,0.0001790539,0.0000390371],"domain_scores_gemma":[0.9996673,0.0001322801,0.00003253774,0.00002867817,0.0000900981,0.00004913179],"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":[0.00007977276,0.00009287291,0.0003041372,0.0002699226,0.00005645095,0.0001928233,0.0002201538,0.5796551,0.009067326,0.3443268,0.001886098,0.0638485],"study_design_scores_gemma":[0.00001516737,0.00006797757,0.00003812978,0.00001812829,0.000007698604,0.00003310313,0.00001516527,0.9683425,0.0009999821,0.0269312,0.003517212,0.00001357062],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001779096,0.00007403029,0.9968777,0.00005462693,0.00002043158,0.00001800098,0.000008240759,0.00004122942,0.001126747],"genre_scores_gemma":[0.1821306,0.0005360365,0.8019631,0.0001364757,0.0001042654,0.000370587,0.0001046715,0.0001348396,0.01451948],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003306251,"threshold_uncertainty_score":0.01106048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02962778358493195,"score_gpt":0.268590283970785,"score_spread":0.2389625003858531,"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."}}