{"id":"W4392943612","doi":"10.1109/icmla58977.2023.00161","title":"Towards Safe Online Machine Learning Model Training and Inference on Edge Networks","year":2023,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Training (meteorology); Inference; Enhanced Data Rates for GSM Evolution; Artificial intelligence; Machine learning; Edge device; Online learning; Multimedia; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.000642815,0.0002371704,0.0002680052,0.0002175161,0.0003298545,0.0001682919,0.000665326,0.0001101359,0.00002542758],"category_scores_gemma":[0.0005057325,0.0002111382,0.00005112744,0.000746417,0.00005742476,0.0003929706,0.0008044648,0.0008353862,0.00003307654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003504338,"about_ca_system_score_gemma":0.00008426482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006062137,"about_ca_topic_score_gemma":0.00002942876,"domain_scores_codex":[0.9982258,0.0001231491,0.0002599965,0.0005682854,0.0003243971,0.0004983373],"domain_scores_gemma":[0.9989659,0.0003819162,0.00009372045,0.0003600286,0.00004729431,0.0001511859],"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":[0.000004872305,0.00001177758,0.0005558899,0.000004581443,0.000007778643,0.00001338743,0.000873487,0.7859385,0.00001432443,0.03461418,0.00005739078,0.1779038],"study_design_scores_gemma":[0.0003333441,0.00009588161,0.001634825,0.00003353766,0.000004517392,0.000005618733,0.00008655711,0.9942255,0.000006908414,0.002757148,0.0005667575,0.000249431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01446611,0.00004346676,0.9759778,0.001459337,0.0002560216,0.000097071,0.000001707008,0.000975588,0.006722885],"genre_scores_gemma":[0.9036808,0.000083999,0.09356502,0.0005448243,0.000145868,0.000006369543,0.00002315776,0.00002526302,0.001924671],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8892147,"threshold_uncertainty_score":0.8609965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05657319367236363,"score_gpt":0.3092488177099152,"score_spread":0.2526756240375516,"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."}}