{"id":"W2963248893","doi":"10.1007/978-3-319-46128-1_50","title":"Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":832,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Convexity; Rate of convergence; Applied mathematics; Mathematics; Stochastic gradient descent; Convergence (economics); Gradient descent; Mathematical proof; Generalization; Simple (philosophy); Convex function; Regular polygon; Mathematical optimization; Computer science; Mathematical analysis; Artificial neural network; Artificial intelligence; Geometry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0238326173554937,"score_gpt":0.2977316453413589,"score_spread":0.2738990279858652,"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."}}