{"id":"W2107479212","doi":"10.1007/s10208-013-9161-0","title":"Restricted Normal Cones and Sparsity Optimization with Affine Constraints","year":2013,"lang":"en","type":"article","venue":"Foundations of Computational Mathematics","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Mathematics; Affine transformation; Convergence (economics); Heuristics; Underdetermined system; Regular polygon; Conic optimization; Mathematical optimization; Optimization problem; Convex optimization; Constraint (computer-aided design); Cone (formal languages); Applied mathematics; Algorithm; Convex analysis; Pure mathematics; Geometry","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":[0.001991526,0.001647139,0.001502957,0.001386708,0.0006519097,0.003017466,0.001886622,0.001413592,0.004585355],"category_scores_gemma":[0.008842263,0.0008700126,0.0008551364,0.002103949,0.003525395,0.004258043,0.002656518,0.004648147,0.0006759334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009887961,"about_ca_system_score_gemma":0.001347224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003323132,"about_ca_topic_score_gemma":0.002789518,"domain_scores_codex":[0.9985653,0.0006471717,0.00005610916,0.0002094179,0.0004472139,0.00007486892],"domain_scores_gemma":[0.996983,0.001896431,0.0003136489,0.0002057132,0.0004308808,0.000170367],"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":[0.00002634519,0.00002684047,0.0001074532,0.0000775666,0.00001537808,0.00004494689,0.00004776302,0.05074088,0.0004217018,0.9345289,0.003035202,0.01092712],"study_design_scores_gemma":[0.00001176812,0.00001567483,0.00006452381,0.00001717812,0.000004648683,0.00003489034,0.00002727921,0.2445067,0.0001685333,0.7524709,0.002663717,0.00001405197],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01003304,0.001619176,0.9673978,0.001259957,0.0002313158,0.00003630579,0.000270049,0.00009302946,0.01905931],"genre_scores_gemma":[0.4827866,0.007904038,0.4574691,0.001124966,0.001924281,0.0004394306,0.001557303,0.0004343496,0.04636002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004585355,"threshold_uncertainty_score":0.01533955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191264359667149,"score_gpt":0.2105095226035655,"score_spread":0.198596879006894,"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."}}