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Second-Order Methods for Stochastic and Nonsmooth Optimization

Description:

The goal of this thesis is to design practical algorithms for nonlinear optimization in the case when the objective function is stochastic or nonsmooth. The thesis is divided into three chapters. Chapter 1 describes an active-set method for the minimization of an objective function that is structurally nonsmooth, viz., it...

Keyword:

machine learning, optimization, deep learning, Newton, nonsmooth, and quasi-Newton

Subject:

Industrial Engineering and Management Sciences

Creator:

Nitish Shirish Keskar

Owner:

Scholarly Digital Publishing

Date Uploaded:

04/16/2018

Date Modified:

04/16/2018

Date Created:

2017-01-01

Resource Type:

Dissertation