{"id":"W1627731299","doi":"10.1145/2746241","title":"Sparse Sums of Positive Semidefinite Matrices","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Algebraic number; Positive-definite matrix; Graph; Preprocessor; Time complexity; Estimator; Spectral properties; Satisfiability","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002164743,0.0001431574,0.0001751347,0.0003180934,0.00006976583,0.00004662197,0.0008158256,0.00007329854,0.00001655466],"category_scores_gemma":[0.00006226384,0.0001391824,0.00007784578,0.0007893485,0.00006706466,0.0003787157,0.00002119034,0.000136129,0.00004531427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006115257,"about_ca_system_score_gemma":0.00007729301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009556544,"about_ca_topic_score_gemma":0.000003104418,"domain_scores_codex":[0.9988248,0.00004996295,0.0002647336,0.0002974045,0.0003697921,0.0001932555],"domain_scores_gemma":[0.9985592,0.0001948183,0.0001136689,0.0007421237,0.0002506652,0.000139518],"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":[0.0001285126,0.001544544,0.0002036943,0.00005754356,0.000348933,0.0000700466,0.009343895,0.06063303,0.0009009324,0.0695389,0.002472373,0.8547576],"study_design_scores_gemma":[0.003994435,0.003672002,0.001454067,0.0003912023,0.0001980019,0.0002937481,0.0008684744,0.6452678,0.2271158,0.1134595,0.001503289,0.001781709],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006039708,0.00006982029,0.9968035,0.0005658775,0.0003740054,0.0001951316,0.00002811932,0.0003356714,0.001023931],"genre_scores_gemma":[0.1951271,0.00004099926,0.8044309,0.0001556147,0.0000191002,0.00003735688,0.00000390262,0.00001454245,0.0001704719],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8529759,"threshold_uncertainty_score":0.5675694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04235669537589582,"score_gpt":0.2740698356254223,"score_spread":0.2317131402495264,"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."}}