{"id":"W2790000037","doi":"10.48550/arxiv.1803.02414","title":"A gradient method in a Hilbert space with an optimized inner product: achieving a Newton-like convergence","year":2018,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Ottawa","funders":"","keywords":"Mathematics; Linear subspace; Gradient descent; Hilbert space; Applied mathematics; Subspace topology; Projection (relational algebra); Convergence (economics); Inner product space; Parameterized complexity; Mathematical analysis; Combinatorics; Algorithm; Pure mathematics; 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":[0.001028779,0.0006779491,0.0006582243,0.0004505054,0.0002753899,0.0006088673,0.0009298083,0.0009117211,0.001322991],"category_scores_gemma":[0.001776486,0.0003163799,0.0004992563,0.0003040533,0.001139288,0.001228698,0.001150759,0.001042583,0.0008269787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003341961,"about_ca_system_score_gemma":0.0008533087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009874607,"about_ca_topic_score_gemma":0.0008315119,"domain_scores_codex":[0.9995719,0.0001430724,0.00001574971,0.00005785232,0.0001854421,0.00002604392],"domain_scores_gemma":[0.9996641,0.0001313221,0.00003253735,0.00003828178,0.00009949179,0.00003423731],"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":[0.0001405128,0.0001506027,0.000991035,0.000527489,0.0001253525,0.0002667163,0.0003428689,0.3509143,0.03963961,0.4195069,0.005787085,0.1816075],"study_design_scores_gemma":[0.00001806162,0.00008783374,0.0001404779,0.00001766883,0.000009454649,0.00009925841,0.000009465439,0.9698991,0.004269308,0.0196877,0.005740904,0.00002076854],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001829799,0.0000825837,0.9968873,0.00005853554,0.00002265227,0.00001395512,0.000005936677,0.0001146138,0.0009846403],"genre_scores_gemma":[0.08253367,0.0003016349,0.9115319,0.0001550055,0.00008748809,0.0001335507,0.00005749101,0.0003216401,0.004877707],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001322991,"threshold_uncertainty_score":0.005440772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08983312980673834,"score_gpt":0.3868919786399844,"score_spread":0.297058848833246,"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."}}