{"id":"W3034386797","doi":"","title":"Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems","year":2020,"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":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Coordinate descent; Variance (accounting); Stochastic gradient descent; Mathematical optimization; Mathematics; Acceleration; Applied mathematics; Computer science; Algorithm; 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":[0.001369037,0.0009958508,0.001400542,0.0004736597,0.000364522,0.001032596,0.001687082,0.001471115,0.002698869],"category_scores_gemma":[0.004097247,0.0005579053,0.0007031829,0.0006627161,0.0009260971,0.001043025,0.001690039,0.002517393,0.001249295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005441961,"about_ca_system_score_gemma":0.001366594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003314829,"about_ca_topic_score_gemma":0.003604582,"domain_scores_codex":[0.999256,0.0002853663,0.0000260077,0.0000897533,0.0002820901,0.00006089401],"domain_scores_gemma":[0.9989471,0.0004337599,0.00007270939,0.0001825988,0.0002720004,0.00009184834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002247709,0.0001402969,0.001098269,0.000213792,0.0001221078,0.0002728588,0.0001500797,0.6447713,0.008943638,0.1268585,0.01721653,0.199988],"study_design_scores_gemma":[0.00001829453,0.0000268446,0.0000484282,0.00000601469,0.000003889632,0.00002678638,0.000002831865,0.9915892,0.0005458033,0.005342462,0.002382364,0.000006988677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00306977,0.0001962019,0.9948068,0.0002166439,0.00008314386,0.00002703869,0.0000243263,0.0004348849,0.001141211],"genre_scores_gemma":[0.1064642,0.0003485711,0.8853713,0.0002928745,0.000228823,0.00021441,0.0001984379,0.0004924359,0.006388917],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003314829,"threshold_uncertainty_score":0.009028614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01061044798547778,"score_gpt":0.203360425388469,"score_spread":0.1927499774029912,"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."}}