{"id":"W2951244983","doi":"10.48550/arxiv.1405.2096","title":"Optimization on the Hierarchical Tucker manifold - applications to tensor completion","year":2014,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Tensor (intrinsic definition); Subspace topology; Mathematical optimization; Overfitting; Manifold (fluid mechanics); Computer science; Conjugate gradient method; Scalability; Algorithm; Optimization problem; Gradient descent; Mathematics; Theoretical computer science; Artificial intelligence; Artificial neural network; Pure mathematics","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":[0.002234702,0.00152569,0.001363451,0.0008902301,0.0006059224,0.001129074,0.00126068,0.001346101,0.002937699],"category_scores_gemma":[0.008505092,0.000563424,0.0009339391,0.001342359,0.00178095,0.002552439,0.001845058,0.002458806,0.001117725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001141029,"about_ca_system_score_gemma":0.001596559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004207028,"about_ca_topic_score_gemma":0.005031621,"domain_scores_codex":[0.9988084,0.0004933689,0.00005796015,0.0002514579,0.0002988119,0.00008999717],"domain_scores_gemma":[0.9970579,0.001664405,0.0002482447,0.000450718,0.0004228773,0.0001558087],"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":[0.00006100129,0.00005725428,0.0003893503,0.0001874791,0.00003981858,0.00007133665,0.00009372806,0.798092,0.004077856,0.1381847,0.003984531,0.05476091],"study_design_scores_gemma":[0.00000490208,0.00001823384,0.00004926885,0.000005825273,0.000002444207,0.00001260293,0.00000808352,0.9611901,0.00069494,0.03701188,0.0009958263,0.000005962404],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002187608,0.0001155485,0.9968945,0.0001249786,0.00001510541,0.00001490034,0.00003995329,0.0001757338,0.000431709],"genre_scores_gemma":[0.144439,0.0006871425,0.8504778,0.0001554467,0.0001488693,0.000189983,0.0004678372,0.0003907418,0.003043302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004207028,"threshold_uncertainty_score":0.01181835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1124153457218306,"score_gpt":0.3412388485841592,"score_spread":0.2288235028623286,"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."}}