{"id":"W3209839293","doi":"10.48550/arxiv.2110.13220","title":"Demystifying and Generalizing BinaryConnect","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Quantization (signal processing); Generalization; Computer science; De facto; Artificial neural network; Convergence (economics); Algorithm; Artificial intelligence; Mathematics; Theoretical computer science","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":[0.00115674,0.0006852481,0.0005794311,0.0008623909,0.0005263639,0.00117829,0.001348928,0.0009441089,0.002990921],"category_scores_gemma":[0.006071168,0.0003037245,0.0003081702,0.0009350521,0.001776627,0.002800597,0.002864275,0.001674696,0.0005038797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007911311,"about_ca_system_score_gemma":0.001154424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0048102,"about_ca_topic_score_gemma":0.005531242,"domain_scores_codex":[0.999436,0.0001156267,0.0000326938,0.0001319283,0.0002393382,0.00004447684],"domain_scores_gemma":[0.9988405,0.0002896374,0.00009457542,0.0003617218,0.0003301479,0.00008340125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001852276,0.0000788976,0.001387997,0.0002688105,0.00005795229,0.0001879006,0.000386078,0.2010627,0.01852689,0.4557317,0.007248321,0.3148775],"study_design_scores_gemma":[0.00002457912,0.0001192492,0.0005570746,0.00003113107,0.0000206329,0.0002398241,0.00004462817,0.8446034,0.00739003,0.1377483,0.009197291,0.00002382749],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03323103,0.000573271,0.9585785,0.0004377199,0.00009874141,0.00007986675,0.0001278728,0.001062724,0.00581022],"genre_scores_gemma":[0.6196016,0.0009293287,0.3696445,0.0005802939,0.0001633054,0.0002127088,0.0003797109,0.0004772749,0.008011303],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0048102,"threshold_uncertainty_score":0.01000565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1077148077294184,"score_gpt":0.2066003936689972,"score_spread":0.09888558593957873,"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."}}