{"id":"W3167047574","doi":"","title":"Distributed Second Order Methods with Fast Rates and Compressed Communication","year":2021,"lang":"en","type":"article","venue":"King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology)","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Sublinear function; Hessian matrix; Newton's method; Rate of convergence; Computer science; Mathematical optimization; Regularization (linguistics); Convergence (economics); Local convergence; Algorithm; Quadratic equation; Newton's method in optimization; Iterative method; Applied mathematics; Mathematics; Artificial intelligence","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":[0.001679716,0.001336792,0.001146343,0.0009085511,0.0005379149,0.001442245,0.00212554,0.001532201,0.003861619],"category_scores_gemma":[0.008864637,0.0006586598,0.0009065031,0.001046949,0.001456774,0.002535049,0.002906467,0.003969579,0.001774352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001150596,"about_ca_system_score_gemma":0.002458284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00291826,"about_ca_topic_score_gemma":0.005285692,"domain_scores_codex":[0.9984478,0.0003923807,0.00006625518,0.0001752176,0.0008160372,0.0001022238],"domain_scores_gemma":[0.9956944,0.00233652,0.0003533518,0.0007736012,0.0006507147,0.0001913631],"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":[0.0002666502,0.0001921451,0.0008197485,0.0004529763,0.00009368029,0.000158279,0.000320598,0.5672393,0.01166922,0.1597554,0.01229168,0.2467404],"study_design_scores_gemma":[0.00002221847,0.00002725683,0.00004269554,0.00001153201,0.000004492398,0.00003294081,0.000009587072,0.9824994,0.001703657,0.01279081,0.002845938,0.000009561333],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001540329,0.0001946025,0.9961986,0.0002315652,0.00005404328,0.00003201153,0.00003088847,0.0003343946,0.001383509],"genre_scores_gemma":[0.1254256,0.0007044849,0.8625422,0.0004021705,0.0003243025,0.0004307038,0.0003300828,0.0005307919,0.009309673],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003861619,"threshold_uncertainty_score":0.01291835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007462794298355328,"score_gpt":0.2176864445366946,"score_spread":0.2102236502383393,"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."}}