{"id":"W2412885812","doi":"","title":"PAC-Bayesian Bounds based on the Rényi Divergence","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Divergence (linguistics); Bayesian probability; Generalization; Kullback–Leibler divergence; Mathematics; Computer science; Applied mathematics; Statistics","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":[0.001775913,0.000349875,0.0002650433,0.0001366502,0.0002923443,0.0002911686,0.001299759,0.0002491733,0.000210132],"category_scores_gemma":[0.0004719644,0.0002672031,0.0001960709,0.000192809,0.0001966053,0.00005600222,0.0005672245,0.0006041444,0.00005727765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001192972,"about_ca_system_score_gemma":0.00009376954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001606426,"about_ca_topic_score_gemma":0.0001550134,"domain_scores_codex":[0.9968312,0.001667626,0.000317707,0.0004768197,0.000373201,0.0003333939],"domain_scores_gemma":[0.9952395,0.001223571,0.0001644448,0.002613243,0.0006492945,0.0001099506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007938721,0.001332061,0.005929379,0.0006186395,0.0007538423,0.0000817616,0.01340366,0.0140278,0.05282063,0.4729345,0.1920351,0.2459833],"study_design_scores_gemma":[0.0003693102,8.466212e-7,0.002149594,0.006647838,0.0000677957,0.000005322453,0.00004693556,0.482686,0.4178769,0.04036159,0.04866659,0.001121293],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02176238,0.0005622062,0.7778632,0.01293272,0.0005929715,0.0005367993,0.00008233673,0.001757263,0.1839101],"genre_scores_gemma":[0.9896781,0.0002722166,0.008065617,0.0002029118,0.00004016251,0.00005117807,0.00006631706,0.00006742102,0.001556093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9679157,"threshold_uncertainty_score":0.999978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01403281663606124,"score_gpt":0.2112830739709972,"score_spread":0.197250257334936,"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."}}