{"id":"W2525766229","doi":"10.1109/tnet.2015.2480418","title":"An Asynchronous Fixed-Point Algorithm for Resource Sharing With Coupled Objectives","year":2015,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Alberta","funders":"","keywords":"Computer science; Subgradient method; Mathematical optimization; Distributed algorithm; Asynchronous communication; Convergence (economics); Gradient descent; Resource allocation; Distributed computing; Algorithm; Mathematics","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":[0.000482623,0.0002689134,0.0002530184,0.0002523523,0.0003954134,0.0002748012,0.001055006,0.0001058693,0.000004370483],"category_scores_gemma":[0.00001266741,0.0002575111,0.00008141036,0.0006317939,0.00006989832,0.0005670036,0.00001431388,0.0002434762,0.000003975799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002300464,"about_ca_system_score_gemma":0.0001057727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003792661,"about_ca_topic_score_gemma":0.00002819107,"domain_scores_codex":[0.9980967,0.00005483804,0.0002938835,0.0007258416,0.0003547957,0.0004739094],"domain_scores_gemma":[0.9981027,0.0002337695,0.0001422336,0.001073512,0.00020366,0.0002441478],"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":[0.0000779942,0.0002633525,0.00003886256,0.00001001941,0.00008117153,0.00001038076,0.002241114,0.6782054,0.00005241447,0.0008565834,0.0001317376,0.318031],"study_design_scores_gemma":[0.0008398566,0.001007948,0.00001685553,0.0001110585,0.00002929934,0.00004458191,0.000168822,0.9926643,0.001232246,0.00309397,0.0004463735,0.0003446956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003798985,0.00005509657,0.9967365,0.0001479155,0.0006676466,0.0006954884,0.000005293139,0.001050307,0.0002618814],"genre_scores_gemma":[0.3094361,0.000005869421,0.6897684,0.0001681777,0.0002481345,0.0002684161,0.000005809597,0.00004571751,0.00005345622],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3176863,"threshold_uncertainty_score":0.9999877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03064657258951903,"score_gpt":0.2694943851431266,"score_spread":0.2388478125536075,"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."}}