{"id":"W2012483518","doi":"10.1016/j.cam.2014.12.011","title":"Vectorial additive half-quadratic minimization for isotropic regularization","year":2014,"lang":"en","type":"article","venue":"Journal of Computational and Applied Mathematics","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"National Natural Science Foundation of China","keywords":"Mathematics; Rate of convergence; Stationary point; Regularization (linguistics); Quadratic equation; Fast Fourier transform; Applied mathematics; Mathematical optimization; Convex function; Minification; Convergence (economics); Regular polygon; Algorithm; Mathematical analysis; Geometry; Computer science","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":[0.001095859,0.0008889219,0.0009935143,0.0004393376,0.0003186293,0.0008048371,0.001368189,0.00148741,0.002561482],"category_scores_gemma":[0.003463341,0.0004607816,0.0005627053,0.000806344,0.001017901,0.001226535,0.00186582,0.002087498,0.0007619809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003549099,"about_ca_system_score_gemma":0.0007863288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001654838,"about_ca_topic_score_gemma":0.002458045,"domain_scores_codex":[0.9993476,0.000245468,0.00003231425,0.00007665069,0.00026441,0.00003357126],"domain_scores_gemma":[0.9988624,0.0006609507,0.00006840669,0.0001437313,0.0002194373,0.00004510523],"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":[0.0001672804,0.0001572779,0.0004124274,0.0005610076,0.0001293356,0.0001560701,0.0002231041,0.4697,0.0166849,0.2608313,0.01688318,0.2340941],"study_design_scores_gemma":[0.000006414647,0.00002212963,0.00005009947,0.000008597059,0.000007434133,0.00004023468,0.00001565934,0.9723892,0.0009748881,0.02473717,0.001740001,0.000008145402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001617736,0.0001236449,0.996852,0.00013575,0.00003426361,0.000008415241,0.00002912458,0.00005409668,0.001145004],"genre_scores_gemma":[0.1347022,0.0006952269,0.8516281,0.0003045187,0.0001715499,0.000153426,0.0003492623,0.0003169309,0.01167881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002561482,"threshold_uncertainty_score":0.008569002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009055277754323118,"score_gpt":0.2136138240724234,"score_spread":0.2045585463181002,"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."}}