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1. 1. Scalable Optimization Methods for Machine Learning : Acceleration, Adaptivity and Structured Non-Convexity

   Författare :Vien Van Mai; Mikael Johansson; John Duchi; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Large-scale optimization; Anderson acceleration; first-order methods; stochastic optimization; momentum; gradient clipping; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : This thesis aims at developing efficient optimization algorithms for solving large-scale machine learning problems. To cope with the increasing scale and complexity of such models, we focus on first-order and stochastic methods in which updates are carried out using only (noisy) information about function values and (sub)gradients. LÄS MER