{"id":"W2951709146","doi":"10.48550/arxiv.1205.6845","title":"Weighted-{$\\ell_1$} minimization with multiple weighting sets","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Weighting; Minification; Mathematics; Combinatorics; Computer science; Algorithm; Mathematical optimization; Physics","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":[0.003094503,0.001771443,0.001186149,0.0007739309,0.0003541325,0.001212405,0.001398104,0.001679636,0.002091554],"category_scores_gemma":[0.01338504,0.0004776323,0.0006263243,0.0008206114,0.001397981,0.002598297,0.002413095,0.001449103,0.000601448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005614217,"about_ca_system_score_gemma":0.000541042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007407096,"about_ca_topic_score_gemma":0.0005615341,"domain_scores_codex":[0.9986672,0.0004732737,0.00008196999,0.0002639345,0.0004182094,0.00009536884],"domain_scores_gemma":[0.9955576,0.003133543,0.000427897,0.00033265,0.00046067,0.00008766814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004547761,0.0001340956,0.001539034,0.0007014785,0.000176456,0.0004033915,0.0002508009,0.6749828,0.02666665,0.1500201,0.002734077,0.1419362],"study_design_scores_gemma":[0.00001242412,0.00007302213,0.0001769074,0.00002685524,0.00001224796,0.00009840869,0.00002908811,0.9746482,0.005339363,0.01878493,0.0007808517,0.00001761622],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01672312,0.000208644,0.9813685,0.0002123572,0.0000232867,0.00003016919,0.00005004019,0.00005306732,0.001330793],"genre_scores_gemma":[0.4558648,0.0007926704,0.5370082,0.0002752963,0.000166786,0.0002788555,0.0004364036,0.0002120973,0.004964837],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003094503,"threshold_uncertainty_score":0.01636553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04503613515933222,"score_gpt":0.1667471518708757,"score_spread":0.1217110167115434,"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."}}