On the Use of Stochastic Hessian Information in Unconstrained Optimization


This paper describes how to incorporate stochastic curvature information in a NewtonCG method and in a limited memory quasi-Newton method for large scale optimization. The motivation for this work stems from statistical learning and stochastic optimization applications in which the objective function is the sum of a very large number of loss terms, and can… (More)

8 Figures and Tables


  • Presentations referencing similar topics