{"id":"W2147795503","doi":"10.1109/pacrim.2009.5291404","title":"Fast Group Sparse Classification","year":2009,"lang":"en","type":"article","venue":"","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Classifier (UML); Optimization problem; Quadratic programming; Greedy algorithm; Computer science; Sparse approximation; Minification; Convex optimization; Mathematical optimization; Linear programming; Linear programming relaxation; Artificial intelligence; Regular polygon; Mathematics; Algorithm","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":[0.001590607,0.001066384,0.001812267,0.001569479,0.000858998,0.001016426,0.001864319,0.002230674,0.005889617],"category_scores_gemma":[0.005543702,0.000396017,0.0006595273,0.002141519,0.0006985881,0.002281328,0.001750658,0.001903413,0.002755104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005646042,"about_ca_system_score_gemma":0.001093229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002163335,"about_ca_topic_score_gemma":0.003463869,"domain_scores_codex":[0.9983945,0.0004231519,0.0000462049,0.0002499563,0.000699285,0.0001868864],"domain_scores_gemma":[0.9971166,0.001170448,0.0002128336,0.0006670218,0.0007356192,0.00009736839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005590636,0.0002099738,0.00137347,0.0001653289,0.00008574498,0.0001585652,0.0001823598,0.07865116,0.007910363,0.02221516,0.0364465,0.8520423],"study_design_scores_gemma":[0.00005278083,0.0001017258,0.0003419811,0.00001419218,0.00001814374,0.0001254631,0.00005186303,0.9647586,0.004103795,0.02292643,0.007492338,0.00001273902],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01125539,0.000423499,0.9836874,0.0004957376,0.0001936065,0.0001419456,0.0002427105,0.001016885,0.002542809],"genre_scores_gemma":[0.2225331,0.0004780922,0.7666935,0.0005951783,0.0004365507,0.000366095,0.001715885,0.0001815403,0.007000106],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005889617,"threshold_uncertainty_score":0.01970273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259576042387802,"score_gpt":0.2293559685876077,"score_spread":0.2067602081637297,"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."}}