{"id":"W3012129924","doi":"10.48550/arxiv.2003.05101","title":"Tensorized Random Projections","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Random projection; Projection (relational algebra); Dimension (graph theory); Rank (graph theory); Gaussian; Tensor (intrinsic definition); Distortion (music); Random matrix; Algorithm; Mathematics; Computer science; Decomposition; Euclidean geometry; Combinatorics; Geometry; Physics","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":[0.001081305,0.001507152,0.0009142086,0.000950995,0.0005007197,0.001655557,0.001288785,0.0009060131,0.00573154],"category_scores_gemma":[0.004957454,0.0005381394,0.0009114471,0.001627164,0.001416983,0.003114021,0.002362767,0.002172792,0.002225787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005799872,"about_ca_system_score_gemma":0.001463975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001402287,"about_ca_topic_score_gemma":0.001447223,"domain_scores_codex":[0.9986954,0.0003639272,0.00006022291,0.0002469989,0.0005084139,0.0001250713],"domain_scores_gemma":[0.998032,0.0005521067,0.0002326698,0.0006376344,0.0003996115,0.0001458135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003523542,0.0001573564,0.001199007,0.0004419585,0.0001457596,0.0004051405,0.0002420755,0.2236825,0.04089214,0.325308,0.01777661,0.3893971],"study_design_scores_gemma":[0.0000262523,0.0001367563,0.0003947244,0.00003533129,0.000026023,0.0003631925,0.00005301144,0.8901655,0.01867964,0.07551251,0.01455584,0.00005120132],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004080961,0.0001887203,0.9932104,0.0001739383,0.00007399772,0.00003111484,0.000192966,0.0005690449,0.001478881],"genre_scores_gemma":[0.1936761,0.001308405,0.7939132,0.0003997293,0.0003907997,0.0002730238,0.001392419,0.0004557753,0.008190603],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00573154,"threshold_uncertainty_score":0.01917398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1888783030525406,"score_gpt":0.2497931122899235,"score_spread":0.06091480923738285,"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."}}