{"id":"W2027711030","doi":"10.1080/02331930008844513","title":"Dykstras algorithm with bregman projections: A convergence proof","year":2000,"lang":"en","type":"article","venue":"Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Okanagan University College; University of British Columbia, Okanagan Campus","funders":"","keywords":"Bregman divergence; Mathematics; Convergence (economics); Algorithm; Regular polygon; Constraint (computer-aided design); Legendre polynomials; Mathematical optimization; Applied mathematics; Mathematical analysis; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001014037,0.0001180695,0.0001059475,0.0001219103,0.0002072314,0.0001708971,0.0002682583,0.0000471433,0.001682648],"category_scores_gemma":[0.00001098922,0.0001002264,0.00003652104,0.001194898,0.00002803118,0.0008688186,0.00002000199,0.00006140061,0.00008604743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003781364,"about_ca_system_score_gemma":0.00009421702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000341334,"about_ca_topic_score_gemma":0.000006983096,"domain_scores_codex":[0.9989882,0.00004815977,0.0001909975,0.0003373882,0.0002792161,0.0001560168],"domain_scores_gemma":[0.9993479,0.00002020727,0.00007356482,0.0002792613,0.0002122422,0.00006688603],"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":[0.000004631179,0.000076702,0.0001044924,0.000002860814,0.00002355575,0.000001855474,0.0001522922,0.9664524,0.000001797638,0.003796981,0.0002498002,0.02913259],"study_design_scores_gemma":[0.0002709696,0.00006198152,0.0001694059,0.000009380741,0.00001507643,0.00001902572,0.00001178559,0.9972625,0.00008447652,0.0001397504,0.001805427,0.0001502225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000585194,0.00001728593,0.9909407,0.001035756,0.00005204056,0.0002081349,0.000003312882,0.0001745425,0.007509661],"genre_scores_gemma":[0.01323319,0.00007941011,0.9782319,0.000356389,0.00005636979,0.00006277335,0.00006899033,0.00001250886,0.007898469],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03081005,"threshold_uncertainty_score":0.99923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005520435647381991,"score_gpt":0.2031312555329953,"score_spread":0.1976108198856133,"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."}}