{"id":"W2774777068","doi":"10.1007/s11590-018-1325-z","title":"“Active-set complexity” of proximal gradient: How long does it take to find the sparsity pattern?","year":2018,"lang":"en","type":"article","venue":"Optimization Letters","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Separable space; Proximal Gradient Methods; Minification; Convex function; Computational intelligence; Regular polygon; Function (biology); Convex optimization","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002600189,0.000210105,0.0002104216,0.0002260757,0.0002772507,0.0001958238,0.001098386,0.00005642973,0.00008881811],"category_scores_gemma":[0.0001133842,0.0001525489,0.00007254673,0.0007613869,0.0004034216,0.0005101622,0.0003252211,0.0001139243,0.00001362957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000736001,"about_ca_system_score_gemma":0.00002778008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003877901,"about_ca_topic_score_gemma":0.00002393422,"domain_scores_codex":[0.998348,0.0001159898,0.0002805003,0.0004851774,0.0004389688,0.0003313852],"domain_scores_gemma":[0.9984865,0.00008567516,0.0002718521,0.0007491958,0.0003009145,0.0001058497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002091848,0.0007016918,0.01369844,0.0001596954,0.0003699553,0.00003349399,0.03635349,0.7820023,0.004780303,0.04380357,0.09725877,0.02062914],"study_design_scores_gemma":[0.0006488523,0.0003473501,0.01159826,0.000100521,0.00003437568,0.00001877449,0.0001548665,0.9619675,0.02311936,0.0003225895,0.001115443,0.0005720878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0086319,0.000002274317,0.9408438,0.04910377,0.0003891351,0.0006619159,0.00002682938,0.0001724348,0.000167909],"genre_scores_gemma":[0.624999,0.000003199375,0.3658255,0.008712905,0.0001527937,0.00006344044,0.00003561095,0.00002585881,0.0001816539],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6163672,"threshold_uncertainty_score":0.6220763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0346326266348508,"score_gpt":0.2504175384860194,"score_spread":0.2157849118511687,"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."}}