{"id":"W4414229121","doi":"10.1109/msp.2025.3557958","title":"Quadratic Transform for Fractional Programming in Signal Processing and Machine Learning: A unified approach for solving optimization problems involving ratios","year":2025,"lang":"en","type":"article","venue":"IEEE Signal Processing Magazine","topic":"Advanced Control Systems Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Fractional programming; Quadratic programming; Signal processing; Maximization; Minification; Margin (machine learning); Optimization problem; Key (lock); Radar","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":[0.003252513,0.001654782,0.001333216,0.001550445,0.0005903266,0.002306469,0.00131908,0.0016672,0.003142589],"category_scores_gemma":[0.006155509,0.000513412,0.001619349,0.002245201,0.002313568,0.0028939,0.001834603,0.004277926,0.001175168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069213,"about_ca_system_score_gemma":0.001235885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00140167,"about_ca_topic_score_gemma":0.001118129,"domain_scores_codex":[0.9983912,0.0007670455,0.00008869616,0.0001806395,0.0004902073,0.00008213237],"domain_scores_gemma":[0.9983844,0.001109925,0.0001107841,0.0001038234,0.0002455487,0.00004558668],"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":[0.00003514403,0.00004270708,0.0001337266,0.000300039,0.0000423463,0.0001056843,0.0001723005,0.125298,0.002205361,0.7833096,0.006538236,0.08181686],"study_design_scores_gemma":[0.00001104255,0.00005884856,0.0000947482,0.00006294591,0.00001650829,0.0001041148,0.00003049982,0.7051532,0.0007985673,0.277496,0.01614597,0.00002759218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005213563,0.001087486,0.9948012,0.0004208572,0.0001248783,0.00001196358,0.00001772764,0.0000389838,0.002975643],"genre_scores_gemma":[0.1079548,0.01044545,0.8653522,0.001001104,0.002450757,0.0003217217,0.0001456852,0.0003951007,0.01193321],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003252513,"threshold_uncertainty_score":0.01720113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0186079600272055,"score_gpt":0.2400353840145565,"score_spread":0.221427423987351,"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."}}