{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009333819,0.000233775,0.000239331,0.0001261261,0.000239967,0.000166693,0.0009638337,0.0001571738,0.00000755621],"category_scores_gemma":[0.00001962962,0.0002925894,0.00009417317,0.0005710499,0.00007028202,0.0003954008,0.003065004,0.0004239467,0.00001127908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009589284,"about_ca_system_score_gemma":0.0000808027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003728542,"about_ca_topic_score_gemma":0.0000218408,"domain_scores_codex":[0.9982777,0.00009148469,0.0001390447,0.001156259,0.00005214986,0.0002833253],"domain_scores_gemma":[0.9984825,0.0001284595,0.0001535851,0.001006065,0.00008278372,0.0001465969],"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":[0.000005227624,0.00004477075,0.001929878,0.00008077842,0.00006705517,0.000598823,0.0002439413,0.517037,0.0009275611,0.4747781,0.0001375925,0.004149315],"study_design_scores_gemma":[0.0002290405,0.0000174287,0.001018451,0.0001032802,0.00004219827,0.00003475041,0.00006238772,0.9341356,0.000437027,0.06268594,0.0007065347,0.0005273297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3238133,0.0003631329,0.674639,0.0002548668,0.0001795039,0.0001397377,0.000001926421,0.0002070285,0.0004015777],"genre_scores_gemma":[0.9715443,0.000661933,0.027202,0.0001864415,0.00006746527,0.000001901284,0.00001057157,0.00001549303,0.0003098354],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6477311,"threshold_uncertainty_score":0.9999526,"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."}}