{"id":"W4408146073","doi":"10.1109/icmla61862.2024.00067","title":"FL-EGM: Decentralized Federated Learning using Aggregator Selection with Enhanced Global Model","year":2024,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"News aggregator; Computer science; Federated learning; Selection (genetic algorithm); Artificial intelligence; Model selection; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002453285,0.0007984384,0.001272004,0.0005515871,0.0005598243,0.001055479,0.002215598,0.001040427,0.001294272],"category_scores_gemma":[0.003396582,0.0003057127,0.0006222424,0.0007402034,0.0006488028,0.002305444,0.00177224,0.001148873,0.0004498507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008990206,"about_ca_system_score_gemma":0.001516918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003721168,"about_ca_topic_score_gemma":0.005269099,"domain_scores_codex":[0.9989799,0.0003087347,0.00005435306,0.0003192582,0.0001933393,0.0001444252],"domain_scores_gemma":[0.9987877,0.0003571229,0.0001278446,0.0003754951,0.0002755921,0.00007615204],"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":[0.0003924801,0.0002402255,0.004718435,0.00008244917,0.0001176265,0.0001419729,0.0001177553,0.7784595,0.003492671,0.008670808,0.005261501,0.1983045],"study_design_scores_gemma":[0.00001209452,0.00003791814,0.0002022053,0.000003818091,0.00000900202,0.00002140025,0.000009241866,0.9946315,0.000789712,0.003761187,0.0005162663,0.000005538679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03917611,0.0003648714,0.9554109,0.0004309987,0.00006606888,0.0000821452,0.0001543381,0.002628216,0.00168638],"genre_scores_gemma":[0.8778242,0.0001557463,0.1179218,0.0003848425,0.000070995,0.0001356346,0.0004283562,0.00009500289,0.002983452],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003721168,"threshold_uncertainty_score":0.01297438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02684954346207328,"score_gpt":0.2914790000292188,"score_spread":0.2646294565671455,"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."}}