{"id":"W7071379344","doi":"","title":"Statistical Divergences for Learning and Inference: Limit Laws and Non-Asymptotic Bounds","year":2022,"lang":"en","type":"dissertation","venue":"ResearchWorks at the University of Washington (University of Washington)","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México; Institute for Catastrophic Loss Reduction","keywords":"Limit (mathematics); Stability (learning theory); Work (physics); Term (time); Calculus (dental); Noise (video)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01581644,0.001733049,0.002407072,0.003761286,0.001118714,0.004688224,0.002528794,0.00295101,0.005066135],"category_scores_gemma":[0.1154836,0.001319331,0.001801699,0.004122261,0.006485528,0.011573,0.00543376,0.0108236,0.001344634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004139899,"about_ca_system_score_gemma":0.002232968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003262879,"about_ca_topic_score_gemma":0.002698146,"domain_scores_codex":[0.9931784,0.003422833,0.0003916715,0.0009334758,0.001792035,0.0002816379],"domain_scores_gemma":[0.8800831,0.105012,0.002445159,0.004817938,0.006376799,0.001265065],"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":[0.00008660978,0.000125267,0.001456542,0.0003618594,0.0001485684,0.0001053126,0.0002579578,0.07858457,0.0006229179,0.8393021,0.006628034,0.07232025],"study_design_scores_gemma":[0.00001110714,0.0000257325,0.0004736909,0.00009063612,0.00002065729,0.00006957004,0.0000259914,0.292845,0.0003268439,0.704057,0.002029809,0.00002388667],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006426394,0.006513982,0.9765302,0.002999222,0.0002588605,0.00003757806,0.0001227434,0.0001845731,0.006926531],"genre_scores_gemma":[0.4500278,0.02701132,0.4843868,0.002503922,0.003682568,0.001060981,0.001334316,0.00132909,0.02866334],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01581644,"threshold_uncertainty_score":0.0836463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01371592093911118,"score_gpt":0.2602309455448983,"score_spread":0.2465150246057871,"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."}}