Title Information
Title
Theory and Computation for Modern Probabilistic Models
Name: Personal
Name Part
Loper, Jackson Hoy
Role
Role Term: Text
creator
Name: Personal
Name Part
Geman, Stuart
Role
Role Term: Text
Advisor
Name: Personal
Name Part
Ramanan, Kavita
Role
Role Term: Text
Reader
Name: Personal
Name Part
Harrison, Matthew
Role
Role Term: Text
Reader
Name: Corporate
Name Part
Brown University. Department of Applied Mathematics
Role
Role Term: Text
sponsor
Origin Information
Copyright Date
2017
Physical Description
Extent
6, 86 p.
digitalOrigin
born digital
Note: thesis
Thesis (Ph. D.)--Brown University, 2017
Genre (aat)
theses
Abstract
Modern probabilistic models involve computation and analysis in very high-dimensional spaces. Here we explore several of ways in which analysis of problems high dimensional spaces can be made more tractable by various reductions. In particular, we focus on finite approximations for sampling point processes, particle methods for sampling high-dimensional distributions, situations in which hitting times for brownian motion in high dimensional space take on particularly simple forms, and certain maximal characteristics on the infinite-dimensional space of couplings of two random variables with fixed marginal distributions.
Subject
Topic
Machine Learning
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01068210")
Topic
Poisson processes
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/00832611")
Topic
Biometry
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/00839765")
Topic
Brownian motion processes
Language
Language Term (ISO639-2B)
English
Record Information
Record Content Source (marcorg)
RPB
Record Creation Date (encoding="iso8601")
20170616
Identifier: DOI
10.7301/Z0668BM7
Access Condition: rights statement (href="http://rightsstatements.org/vocab/InC/1.0/")
In Copyright
Access Condition: restriction on access
Collection is open for research.
Type of Resource (primo)
dissertations