{"id":"W4318186088","doi":"10.1109/bigdata55660.2022.10020426","title":"A Convergence Theory for Federated Average: Beyond Smoothness","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Big Data (Big Data)","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of British Columbia Hospital","funders":"","keywords":"Smoothness; Computer science; Lipschitz continuity; Convergence (economics); Bounded function; Function (biology); Gradient descent; Mathematical optimization; Scheme (mathematics); Stochastic gradient descent; Applied mathematics; Mathematics; Artificial intelligence; Artificial neural network; Mathematical analysis","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":[0.01287062,0.002972136,0.003308933,0.003186401,0.001812927,0.003198568,0.00425962,0.002964424,0.00538445],"category_scores_gemma":[0.05411834,0.001068776,0.003835653,0.002938734,0.004820506,0.007911771,0.005842644,0.008657575,0.00121361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003395754,"about_ca_system_score_gemma":0.003131595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003876083,"about_ca_topic_score_gemma":0.002029018,"domain_scores_codex":[0.9953828,0.001574914,0.0002561368,0.001074141,0.001269455,0.0004424611],"domain_scores_gemma":[0.9679183,0.02243644,0.001540015,0.002539256,0.004609753,0.0009562347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003343218,0.0001450914,0.002304552,0.0005230221,0.0001855576,0.0002721119,0.0003971181,0.3924459,0.002248563,0.5508825,0.007086073,0.04317515],"study_design_scores_gemma":[0.00001720768,0.00006944041,0.0002072194,0.0000732327,0.00003350392,0.00008327382,0.0000380433,0.8609276,0.000734864,0.1362446,0.001545739,0.000025321],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006333806,0.0008519553,0.9888055,0.0008049782,0.00009117497,0.00006134855,0.0001168696,0.0002871802,0.002647219],"genre_scores_gemma":[0.5751334,0.005236943,0.4015481,0.001833173,0.0007500913,0.001163878,0.0008822639,0.0011376,0.01231459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01287062,"threshold_uncertainty_score":0.06806713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2782544865332073,"score_gpt":0.3560469689397069,"score_spread":0.07779248240649961,"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."}}