{"id":"W1545380151","doi":"10.1002/9781118884003.ch2","title":"Optimization algorithms—an overview","year":2014,"lang":"en","type":"other","venue":"","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Hessian matrix; Conjugate gradient method; Newton's method; Focus (optics); Newton's method in optimization; Gradient descent; Point (geometry); Computer science; Quasi-Newton method; Gauss; Algorithm; Mathematics; Function (biology); Minification; Mathematical optimization; Nonlinear conjugate gradient method; Nonlinear system; Applied mathematics; Iterative method; Local convergence; Artificial intelligence; Geometry","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":[0.002007779,0.001883439,0.001507633,0.002546832,0.0005975771,0.003243322,0.001654872,0.002236329,0.01160166],"category_scores_gemma":[0.003762213,0.001081296,0.001336831,0.004651369,0.001471259,0.004244776,0.001776878,0.004044749,0.0109657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001286894,"about_ca_system_score_gemma":0.001593699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001763633,"about_ca_topic_score_gemma":0.0009794702,"domain_scores_codex":[0.9983248,0.0004170176,0.0001596219,0.0002703205,0.0007610859,0.00006720458],"domain_scores_gemma":[0.9986098,0.0008273773,0.00005597532,0.0001342567,0.0003234379,0.00004921616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004530417,0.0001419191,0.0004614923,0.002978589,0.0001052452,0.0001240631,0.0001443365,0.0190692,0.0008535016,0.2593906,0.05482846,0.6618572],"study_design_scores_gemma":[0.00001363391,0.00008032429,0.0004858499,0.001151501,0.00002906956,0.0004758546,0.00005552472,0.01576554,0.0005270466,0.163397,0.8179787,0.00003994112],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008149541,0.6017474,0.3191708,0.003442023,0.002173056,0.0001144179,0.0003276075,0.0007309922,0.07147875],"genre_scores_gemma":[0.0170547,0.7501872,0.1920634,0.001754734,0.004884657,0.0003671726,0.0008185455,0.0006023396,0.03226718],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01160166,"threshold_uncertainty_score":0.03881139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1228800191125163,"score_gpt":0.4240585033542926,"score_spread":0.3011784842417762,"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."}}