{"id":"W2188090572","doi":"10.1007/bfb0006694","title":"Differentiability of Min Max and saddle points under relaxed assumptions","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in control and information sciences","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Infimum and supremum; Differentiable function; Saddle point; Mathematics; Saddle; Pure mathematics; Object (grammar); Sensitivity (control systems); Mathematical economics; Mathematical analysis; Applied mathematics; Mathematical optimization; Computer science; Geometry; Engineering; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0004764206,0.000154224,0.0002770312,0.0003999244,0.0001437566,0.0002018242,0.0002535182,0.0001525994,0.0001122343],"category_scores_gemma":[0.0001544528,0.0001182429,0.00005766322,0.0001725347,0.0002239805,0.001568085,0.0000802486,0.00014155,0.000006100327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002775507,"about_ca_system_score_gemma":0.00007772336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002416739,"about_ca_topic_score_gemma":0.00008878511,"domain_scores_codex":[0.9987826,0.00003141841,0.0004937362,0.0002139647,0.0003575819,0.0001207201],"domain_scores_gemma":[0.9989207,0.0003789871,0.0003265238,0.0001678009,0.0001541304,0.00005185409],"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":[0.00001598177,0.00002936163,0.001873972,0.0000581903,0.00006320957,1.806226e-7,0.0009777173,0.02624459,0.00002178415,0.8646198,0.0000359739,0.1060592],"study_design_scores_gemma":[0.001050957,0.00009817025,0.0215812,0.00008052692,0.00005037611,0.000006572755,0.00001170159,0.8000868,0.00002044661,0.1700457,0.006605334,0.0003621979],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003523283,0.0003177281,0.97573,0.006288654,0.000088439,0.000194447,0.0000312498,0.00002496159,0.01697219],"genre_scores_gemma":[0.9793698,0.0003250068,0.01750606,0.002008812,0.00003845911,0.000007127664,0.00002448649,0.000003473551,0.0007167686],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9790175,"threshold_uncertainty_score":0.4821807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01262433140779353,"score_gpt":0.2311896777789595,"score_spread":0.218565346371166,"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."}}