{"id":"W7132903521","doi":"","title":"Accelerating Internet Scale Distributed Machine Learning","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cloud computing; Throughput; Overlay network; Scale (ratio); The Internet; Distributed learning; Pipeline transport; Distributed algorithm","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":[0.00247942,0.0006415442,0.0006143171,0.0005714881,0.0007986367,0.00138595,0.00143198,0.0007382083,0.002423683],"category_scores_gemma":[0.009675949,0.000298096,0.0003640243,0.0008266888,0.001069822,0.003066871,0.00249071,0.001745941,0.0006580505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001549903,"about_ca_system_score_gemma":0.002013856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004499343,"about_ca_topic_score_gemma":0.005199555,"domain_scores_codex":[0.9987395,0.0003818178,0.00003714352,0.0002736477,0.000369071,0.000198735],"domain_scores_gemma":[0.9954443,0.002381791,0.0002102489,0.001319204,0.0004378764,0.0002065795],"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":[0.0002921658,0.0002564291,0.00279662,0.00008535016,0.00004946854,0.00008863889,0.0001462914,0.8322131,0.006211089,0.03162238,0.01271954,0.1135189],"study_design_scores_gemma":[0.00001295863,0.00001734005,0.0001299678,0.000001696987,0.000003148949,0.00000686269,0.0000172637,0.9884722,0.001241096,0.009244969,0.0008499532,0.000002547952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1883638,0.0007480757,0.7868729,0.00241786,0.0002920296,0.0001764956,0.0002751584,0.01047998,0.01037378],"genre_scores_gemma":[0.8714373,0.0002144354,0.1247634,0.0002156062,0.00006749832,0.0001263626,0.0004292607,0.0002553896,0.002490658],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004499343,"threshold_uncertainty_score":0.0131126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04069754515560428,"score_gpt":0.3360528138045115,"score_spread":0.2953552686489073,"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."}}