{"id":"W2809954131","doi":"10.1109/isit.2018.8437473","title":"Hierarchical Coded Computation","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Computation; Erasure; Matrix multiplication; Algorithm; Erasure code; Multiplication (music); Partition (number theory); Matrix (chemical analysis); Coding (social sciences); Theoretical computer science; Decoding methods; Mathematics","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":[0.0006022499,0.0004761901,0.0004784147,0.0005148587,0.0006090094,0.0009260848,0.00122845,0.0005392349,0.005254089],"category_scores_gemma":[0.00319967,0.0002570905,0.0004319285,0.0006711787,0.0009633977,0.001305535,0.001373813,0.001003856,0.0008571776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325599,"about_ca_system_score_gemma":0.002158449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005159386,"about_ca_topic_score_gemma":0.007502485,"domain_scores_codex":[0.9994286,0.0001107505,0.00002475708,0.00008509147,0.0002387788,0.0001120144],"domain_scores_gemma":[0.9985695,0.0004306755,0.00009314607,0.0004861338,0.0003373735,0.00008324775],"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":[0.000341881,0.00009243617,0.001083479,0.0002484774,0.0000521892,0.0001546404,0.0002806733,0.5270504,0.0215788,0.2674585,0.01200342,0.1696551],"study_design_scores_gemma":[0.00001791134,0.00003653468,0.0001175062,0.00001244249,0.00000801054,0.00002763593,0.00001731873,0.9659947,0.004365256,0.02546751,0.003923796,0.00001143679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01927101,0.0002262821,0.9713295,0.0002041236,0.00008446897,0.0000825942,0.0001037911,0.0008798445,0.007818501],"genre_scores_gemma":[0.5478467,0.0002624248,0.4401054,0.0002432916,0.00006070868,0.0002424427,0.0002277844,0.0001995109,0.01081167],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005254089,"threshold_uncertainty_score":0.01757669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02971116508146374,"score_gpt":0.2920405706126319,"score_spread":0.2623294055311682,"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."}}