{"id":"W2982518953","doi":"10.48550/arxiv.1910.13650","title":"Bundle methods for dual atomic pursuit","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bundle; Duality (order theory); Dual (grammatical number); Set (abstract data type); Sequence (biology); Gauge (firearms); Duality gap; Mathematics; Optimization problem; Algorithm; Mathematical optimization; Computer science; Combinatorics; Chemistry; Materials 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":[0.00189949,0.001030975,0.001078714,0.001204932,0.0006505207,0.001364356,0.001146825,0.001431287,0.005142643],"category_scores_gemma":[0.005020056,0.0006152089,0.0009644217,0.00129605,0.001864344,0.001994029,0.003309601,0.003116847,0.001800274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00072593,"about_ca_system_score_gemma":0.0008720543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007952069,"about_ca_topic_score_gemma":0.0008783478,"domain_scores_codex":[0.9989613,0.0004934242,0.0000333414,0.0001281913,0.0003179043,0.0000657196],"domain_scores_gemma":[0.9986762,0.0006666064,0.0001089352,0.0002516655,0.0002111652,0.00008536754],"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":[0.0001299528,0.00007380627,0.0004443097,0.0001849403,0.00007577099,0.00007343612,0.0001459474,0.1440432,0.006761199,0.7219936,0.005155875,0.1209178],"study_design_scores_gemma":[0.00001922783,0.00005578863,0.00007669686,0.00002298673,0.000006899795,0.00005159512,0.00002028864,0.7464818,0.001721758,0.2456664,0.005861353,0.00001530693],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001441197,0.0001647909,0.9966902,0.0001077698,0.0000290427,0.00001711901,0.00002524072,0.0001035409,0.001421067],"genre_scores_gemma":[0.109634,0.0008647834,0.8821095,0.0002421269,0.0002088523,0.0003012479,0.0002699386,0.0003037682,0.006065755],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005142643,"threshold_uncertainty_score":0.01720381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09574137947842264,"score_gpt":0.2375950047311853,"score_spread":0.1418536252527627,"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."}}