{"id":"W4385444778","doi":"10.1109/tsmc.2023.3293462","title":"FedStream: Prototype-Based Federated Learning on Distributed Concept-Drifting Data Streams","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Systems","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Fundamental Research Funds for the Central Universities; Sichuan Province Science and Technology Support Program; Fok Ying Tong Education Foundation; National Natural Science Foundation of China","keywords":"Data stream mining; Computer science; Federated learning; Focus (optics); Metric (unit); Streaming data; Distributed learning; Data stream; STREAMS; Transformation (genetics); Data mining; Data science; Distributed computing; Computer network","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":[0.00575419,0.001094233,0.001997764,0.001338415,0.0008359,0.001469294,0.0041034,0.001451607,0.001289245],"category_scores_gemma":[0.01252717,0.0005416462,0.0008259487,0.001667583,0.001078797,0.005262497,0.00352044,0.002037965,0.000429428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001029508,"about_ca_system_score_gemma":0.001893416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003356079,"about_ca_topic_score_gemma":0.002623063,"domain_scores_codex":[0.9980968,0.0005024686,0.0001459343,0.0005586572,0.0005564399,0.0001397001],"domain_scores_gemma":[0.9954728,0.001552151,0.0002823866,0.001227677,0.001200705,0.0002641976],"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":[0.0008057967,0.0006565275,0.004236878,0.0001854445,0.0002055885,0.000281493,0.0003218796,0.299662,0.005795979,0.009113031,0.007234814,0.6715006],"study_design_scores_gemma":[0.00004044913,0.00007962761,0.0001356389,0.000004982519,0.000009790828,0.00005332131,0.0000219217,0.9905604,0.001572761,0.006940364,0.0005717564,0.000008956286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02955721,0.0003523052,0.9645039,0.0001977382,0.00009842334,0.0001913194,0.0001567859,0.004467342,0.0004749204],"genre_scores_gemma":[0.6006548,0.000300122,0.3956068,0.0003024569,0.00009487686,0.0003966427,0.0009010736,0.0002100478,0.001533138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00575419,"threshold_uncertainty_score":0.03043139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04251270373771712,"score_gpt":0.2751769021600894,"score_spread":0.2326641984223723,"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."}}