{"id":"W4399951357","doi":"10.1109/iotm.001.2300285","title":"Efficient Transformer-Based Hyper-Parameter Optimization for Resource-Constrained IoT Environments","year":2024,"lang":"en","type":"article","venue":"IEEE Internet of Things Magazine","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Transformer; Internet of Things; Mathematical optimization; Distributed computing; Electrical engineering; Embedded system; Engineering; Mathematics; Voltage","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":[0.0007595927,0.001005442,0.0008015671,0.0003574581,0.0002800545,0.0008783186,0.001205753,0.0007573741,0.002077568],"category_scores_gemma":[0.002622868,0.000492505,0.0004548033,0.0003156743,0.0007458979,0.001681692,0.001397406,0.001507349,0.0004564988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007833559,"about_ca_system_score_gemma":0.001087584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004389324,"about_ca_topic_score_gemma":0.006899315,"domain_scores_codex":[0.9997211,0.0000761385,0.00001550824,0.00006784905,0.00006050605,0.00005887423],"domain_scores_gemma":[0.9994304,0.0003240576,0.00006060353,0.00007178867,0.00007445232,0.00003870426],"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":[0.00008235476,0.00005850072,0.000851794,0.00005838813,0.00003666122,0.0001135659,0.00004969866,0.9217951,0.003889872,0.004425814,0.001604746,0.06703348],"study_design_scores_gemma":[0.000003581377,0.000008829721,0.00003271232,0.000001961729,0.000002851817,0.000007806608,0.000005288446,0.9977797,0.0004361544,0.001562093,0.0001572567,0.000001767257],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05117611,0.0005457936,0.9412881,0.0002958508,0.00005833886,0.00006209666,0.000065513,0.00204119,0.004466973],"genre_scores_gemma":[0.8905382,0.000201608,0.1065701,0.0001900965,0.00002839937,0.00007928831,0.0001661009,0.0002772453,0.00194897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004389324,"threshold_uncertainty_score":0.008727551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411798135094935,"score_gpt":0.2394669604499392,"score_spread":0.2253489790989899,"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."}}