{"id":"W3109568406","doi":"10.48550/arxiv.2007.02916","title":"On the Asymptotic Linear Convergence Speed of Anderson Acceleration Applied to ADMM","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Numerical methods in inverse problems","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Acceleration; Convergence (economics); Stationary point; Mathematics; Applied mathematics; Mathematical optimization; Mathematical analysis; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004797532,0.0003369972,0.0005342964,0.0001321447,0.00009932874,0.00002571113,0.0009081126,0.0002611764,0.0004276776],"category_scores_gemma":[0.0009251286,0.0003007215,0.0001968729,0.0005906843,0.0001371934,0.00004883419,0.0007844668,0.0007175371,0.0002186351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001633102,"about_ca_system_score_gemma":0.0001061559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003053419,"about_ca_topic_score_gemma":0.000005169438,"domain_scores_codex":[0.9981649,0.0002666231,0.0003433663,0.0007785133,0.0001822377,0.0002643944],"domain_scores_gemma":[0.9970575,0.001270003,0.0004278104,0.0009250135,0.000142349,0.0001772969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003027081,0.0001660086,0.000152187,0.0004388678,0.0002115957,0.00002636064,0.0008469616,0.05463227,0.003034148,0.9376786,0.002360108,0.0001502156],"study_design_scores_gemma":[0.000472992,0.0001744257,0.00006414722,0.0002118562,0.0002364894,6.416942e-7,0.0004672747,0.1114091,0.01325438,0.8730597,0.00015555,0.0004935127],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3815176,0.00000529835,0.6016987,0.0007942335,0.0006539134,0.001734031,0.00003359047,0.0002030881,0.01335958],"genre_scores_gemma":[0.9808037,0.00001957697,0.01821092,0.0004326076,0.00008185782,0.000002522172,0.000006536675,0.0000424893,0.0003997619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5992861,"threshold_uncertainty_score":0.9999445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3418236069353364,"score_gpt":0.2798873531040792,"score_spread":0.06193625383125723,"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."}}