{"id":"W3035695586","doi":"10.1109/cvpr42600.2020.00162","title":"ReSprop: Reuse Sparsified Backpropagation","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Speedup; Computer science; Computation; Backpropagation; Convolutional neural network; Convolution (computer science); Reuse; Parallel computing; Reduction (mathematics); Sparse matrix; Computational science; Artificial neural network; Artificial intelligence; Algorithm; Computer engineering; 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":[0.0004488116,0.001022486,0.000495301,0.0004078886,0.0002647432,0.0005719531,0.001790152,0.0006857541,0.0059268],"category_scores_gemma":[0.001791811,0.0003992706,0.0004653,0.0004784386,0.0003771244,0.001231978,0.001213704,0.001361942,0.002522433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003670615,"about_ca_system_score_gemma":0.001228698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003670095,"about_ca_topic_score_gemma":0.007238192,"domain_scores_codex":[0.9996743,0.00003109068,0.00001709944,0.00007049562,0.000156564,0.00005049009],"domain_scores_gemma":[0.9995717,0.0001015689,0.00004019587,0.000139389,0.000114292,0.00003292373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006234696,0.0003286437,0.002564116,0.0002998751,0.0001835925,0.000423777,0.0001390695,0.2378009,0.06689948,0.01855688,0.04459119,0.6275889],"study_design_scores_gemma":[0.00004996024,0.00008058833,0.0002755208,0.00001132488,0.00001263791,0.0001326582,0.00001129858,0.9678786,0.02151821,0.003275156,0.006740293,0.0000137349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03919539,0.0004005495,0.9285383,0.0003099602,0.0002436184,0.0001203955,0.0004444341,0.0232371,0.007510322],"genre_scores_gemma":[0.2904076,0.0003644294,0.6921932,0.0004345965,0.0001004328,0.0002442026,0.002201495,0.00175977,0.01229439],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0059268,"threshold_uncertainty_score":0.01982707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05164835959100823,"score_gpt":0.2591902171441513,"score_spread":0.2075418575531431,"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."}}