Optimisation problem, solvers, challenges and research directions -- Mini-batch and block-coordinate approach -- Variance reduction methods -- Learning and data access -- Mini-batch block-coordinate Newton method -- Stochastic trust region inexact Newton method -- Conclusion and future scope.

"Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research directions to tackle the challenge. Developed optimisation techniques are also explored to improve machine learning algorithms based on data access and on first and second order optimisation methods. The book will be a valuable reference to practitioners and researchers as well as students in the field of machine learning"-- Provided by publisher.

OCLC-licensed vendor bibliographic record.