A Minibatch Proximal Stochastic Recursive Gradient Algorithm Using a Trust-Region-Like Scheme and Barzilai-Borwein Stepsizes

A Minibatch Proximal Stochastic Recursive Gradient Algorithm Using a Trust-Region-Like Scheme and Barzilai-Borwein Stepsizes

We consider the problem of minimizing the sum of an average of a large number of smooth convex component functions and a possibly nonsmooth convex function that admits a simple proximal mapping. This class of problems arises frequently in machine learning, known as regularized empirical risk minimiz...

Full description

Bibliographic Details
Main Authors: Yu, T., Liu, X.W., Dai, Y.H., Sun, Jie
Format: Journal Article
Language:English
Published: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC 2021
Subjects:
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Hardware & Architecture
Computer Science, Theory & Methods
Engineering, Electrical & Electronic
Computer Science
Engineering
Convergence
Convex functions
Risk management
Gradient methods
Learning systems
Sun
Barzilai-Borwein (BB) method
empirical risk minimization (ERM)
proximal method
stochastic gradient
trust-region
MACHINE
Online Access:http://hdl.handle.net/20.500.11937/91427

Internet

http://hdl.handle.net/20.500.11937/91427

Similar Items