Index Catalog // Arch : Northwestern University Institutional Repository

Start Over

Filtering by: Keyword Reinforcement Learning Keyword Statistical Learning Keyword Stochastic Gradient Descent Keyword Uncertainty Quantification Subject Statistics

1 entry found

List Gallery Masonry Slideshow

1. Asymptotic Uncertainty Quantification and Its Application in Efficient Sampling and Learning

Description:: The ever growing desire for accurate estimation and efficient learning necessitates the efforts to quantitatively characterize uncertainties for models. In this thesis, four problems pertaining to uncertainty quantification are discussed: A sequential stopping framework of constructing fixed-precision confidence regions is proposed for a class of multivariate simulation problems where variance...
Keyword:: Ranking and Selection, Reinforcement Learning, Statistical Learning, Stochastic Gradient Descent, and Uncertainty Quantification
Subject:: Applied mathematics, Statistics, and Computer science
Creator:: Zhu, Yi
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 01/21/2021
Date Created:: 2020-01-01
Resource Type:: Dissertation
Alternate Identifier:: http://dissertations.umi.com/northwestern:15080 and etdadmin_upload_741745

LIBRARIES | ARCH

Limit your search

Type

Resource type

Creator

Keyword

Subject

Language

1. Asymptotic Uncertainty Quantification and Its Application in Efficient Sampling and Learning

Limit your search

Type

Resource type

Creator

Keyword

Subject

Language

Search Constraints

Search Results

1. Asymptotic Uncertainty Quantification and Its Application in Efficient Sampling and Learning