{"id":"W3089190316","doi":"10.48550/arxiv.2009.11359","title":"A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematics; Rate of convergence; Upper and lower bounds; Acceleration; Quadratic equation; Applied mathematics; Convergence (economics); Mathematical optimization; Multiplicative function; Quadratic growth; Monotone polygon; Computer science; Algorithm; Mathematical analysis; Key (lock)","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":[0.004783494,0.001997457,0.001095078,0.001111857,0.0006564582,0.00182822,0.001631381,0.001781544,0.004457634],"category_scores_gemma":[0.01602674,0.0007113429,0.001266811,0.0007218266,0.002847753,0.002494584,0.002492707,0.005400695,0.0007017329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002201838,"about_ca_system_score_gemma":0.002773942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003801752,"about_ca_topic_score_gemma":0.002953618,"domain_scores_codex":[0.9981328,0.0006126614,0.0000803728,0.0002196312,0.0007834735,0.0001710752],"domain_scores_gemma":[0.9917583,0.005985869,0.0004283292,0.0003781937,0.001212452,0.0002368807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005364361,0.0000496905,0.0003379859,0.0002874891,0.00004189974,0.00006579012,0.0002071145,0.5965648,0.002847395,0.3731504,0.001437077,0.02495667],"study_design_scores_gemma":[0.000004587504,0.00002390467,0.00003023936,0.00001666611,0.000005159583,0.000009512649,0.000007919727,0.9749022,0.0004341569,0.02380529,0.0007546272,0.000005816885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001452993,0.0001952471,0.9953216,0.0001653257,0.00003411584,0.00003235431,0.00001355968,0.00003543645,0.002749422],"genre_scores_gemma":[0.4065694,0.001684913,0.5703815,0.0005536485,0.0003511232,0.0006971933,0.0001607087,0.0003707171,0.01923084],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004783494,"threshold_uncertainty_score":0.02529782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09099843152611485,"score_gpt":0.248063739770736,"score_spread":0.1570653082446211,"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."}}