{"id":"W4392404031","doi":"10.23952/jano.6.2024.1.07","title":"On the linear convergence rate of generalized ADMM for convex composite programming","year":2024,"lang":"en","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Henan Province; National Natural Science Foundation of China","keywords":"Convergence (economics); Rate of convergence; Mathematics; Composite number; Regular polygon; Mathematical optimization; Applied mathematics; Linear programming; Computer science; Algorithm; Economics; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01851027,0.002537047,0.001416511,0.002037488,0.0008852645,0.001866765,0.002202454,0.002005599,0.00436453],"category_scores_gemma":[0.04750597,0.0008386481,0.001742656,0.00150269,0.004646477,0.004405744,0.004176737,0.007846321,0.001196135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002010064,"about_ca_system_score_gemma":0.001534293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002588932,"about_ca_topic_score_gemma":0.001555382,"domain_scores_codex":[0.994458,0.003245608,0.0001851469,0.0005475517,0.001212555,0.0003511284],"domain_scores_gemma":[0.9726293,0.02219914,0.0008484073,0.001257362,0.002659848,0.0004059842],"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":[0.0006577002,0.000125911,0.001891977,0.001215135,0.0002197683,0.0004454365,0.0006372849,0.33624,0.007260566,0.5641035,0.00967906,0.07752373],"study_design_scores_gemma":[0.00002876704,0.000139978,0.0002301715,0.000160604,0.0000373723,0.0001474395,0.00006099653,0.902935,0.002722202,0.090119,0.003385957,0.00003252525],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01100045,0.006785928,0.9652756,0.001689108,0.0002666357,0.00008221457,0.00009830754,0.000305359,0.01449646],"genre_scores_gemma":[0.4515147,0.01207099,0.5150042,0.001922743,0.001233704,0.0009292144,0.000566802,0.001032677,0.01572505],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01851027,"threshold_uncertainty_score":0.09789282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01303720675804006,"score_gpt":0.2509826683118481,"score_spread":0.2379454615538081,"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."}}