{"id":"W4399169098","doi":"10.1109/tcomm.2024.3407208","title":"Decentralized Federated Learning Over Imperfect Communication Channels","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Imperfect; Computer science; Computer network; Telecommunications; Distributed computing","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0005497875,0.0002363482,0.0002010747,0.0003972652,0.001284189,0.0009067216,0.02239392,0.0001812684,0.00009147028],"category_scores_gemma":[0.0004881219,0.0002443666,0.0001445785,0.001491225,0.0002265563,0.001153791,0.001543376,0.001338449,0.0003023816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002301068,"about_ca_system_score_gemma":0.0001266604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001433845,"about_ca_topic_score_gemma":0.00009391607,"domain_scores_codex":[0.9979931,0.0005070141,0.0003844117,0.0004703148,0.0002763307,0.0003688505],"domain_scores_gemma":[0.9849327,0.001095871,0.00007443458,0.01370587,0.0001032398,0.0000878383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005788451,0.001705193,0.00005693889,0.0001723758,0.001016691,0.00002735389,0.002826269,0.0103796,0.01690174,0.05288966,0.14475,0.7692163],"study_design_scores_gemma":[0.0002987305,0.00007488921,0.00003219462,0.0002035245,0.00003417141,0.00002710624,0.00005970642,0.9278833,0.01024319,0.02229048,0.03851493,0.0003378167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001543323,0.002173682,0.9533726,0.03644192,0.0006056087,0.0003356637,0.00002671718,0.003956347,0.001544151],"genre_scores_gemma":[0.911336,0.006066633,0.08186901,0.0001540516,0.000008836968,0.0002155535,0.00003757917,0.00003402901,0.000278283],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9175037,"threshold_uncertainty_score":0.996498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04205023638544281,"score_gpt":0.3145488807666332,"score_spread":0.2724986443811904,"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."}}