{"id":"W2739627855","doi":"10.24963/ijcai.2017/363","title":"Optimizing Ratio of Monotone Set Functions","year":2017,"lang":"en","type":"article","venue":"","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Novelis (Canada)","funders":"National Natural Science Foundation of China","keywords":"Submodular set function; Monotone polygon; Set function; Set (abstract data type); Mathematics; Greedy algorithm; Approximation algorithm; Combinatorics; Discrete mathematics; Mathematical optimization; Upper and lower bounds; Applied mathematics; Computer science; Mathematical analysis","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":[0.0001092653,0.00004963809,0.00008025925,0.00004378882,0.0003827074,0.000163196,0.0008009049,0.00001923861,0.00005955843],"category_scores_gemma":[0.00002393518,0.00004461719,0.00004866175,0.00005603236,0.00007278596,0.0004809572,0.0003067149,0.0000505779,0.00002878295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004620063,"about_ca_system_score_gemma":0.00002043163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008664273,"about_ca_topic_score_gemma":0.00001813635,"domain_scores_codex":[0.9995412,0.00001018081,0.0001057368,0.000144579,0.0001014933,0.00009685617],"domain_scores_gemma":[0.9989862,0.00002668636,0.00007769918,0.0008267226,0.00004858214,0.00003413986],"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":[0.00000441992,0.0001038463,0.0007018211,0.0000138854,0.0000444654,0.000006374675,0.0009744744,0.00170542,0.001477989,0.9122187,0.007553213,0.0751954],"study_design_scores_gemma":[0.0003436673,0.0000731586,0.004389043,0.00001567419,0.000005619619,0.000007982273,0.00005643028,0.9540652,0.00713097,0.02656353,0.007171503,0.0001772075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002447659,0.00001636422,0.9762036,0.0006214691,0.0005788871,0.00004738866,0.000002120323,0.00006072716,0.02002176],"genre_scores_gemma":[0.5496407,0.000004354931,0.4485621,0.00006364964,0.00006439834,0.000004730628,8.912261e-7,0.000002266725,0.001656909],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9523598,"threshold_uncertainty_score":0.2943515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05506663702558866,"score_gpt":0.2910248506300271,"score_spread":0.2359582136044384,"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."}}