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Now showing items 121-130 of 212
Characterizing Posterior Uncertainty for the Indian Buffet Process
(2017-07-14)
Many problems in data science and machine learning require identifying latent features that occur in a set of observations. For example, given a set of images, we may want to determine what objects are contained in each ...
Modeling Musical Influence Through Data
(2018-06-29)
Musical influence is a topic of interest and debate among critics, historians, and general listeners alike, yet to date there has been limited work done to tackle the subject in a quantitative way. In this thesis, we address ...
The Algorithmic Foundations of Private Computational Social Science
(2022-08-12)
Social scientists, political scientists, economists, and healthcare researchers crucially rely on statistical methods to further the study of individuals, society, and human behavior via inferential analysis. Unfortunately, ...
Robust Methods for Estimating the Intraclass Correlation Coefficient and for Analyzing Recurrent Event Data
(2018-09-25)
Robust statistics have emerged as a family of theories and techniques for estimating parameters of a model while dealing with deviations from idealized assumptions. Examples of deviations include misspecification of ...
Select Works on the Economics of Education
(2022-05-04)
This dissertation comprises three essays in the field of economics of education. The first essay studies the short and long-run effects of Head Start, a federally funded early childhood education program that targets ...
Invariance versus Adversarial Learning in Domain Generalization with Applications to Neuroscience
(2022-05-23)
We explore the practical application of two modern domain
invariant representation-learning techniques for addressing the domain
generalization problem in statistical machine learning. Specifically, we
investigate the ...
Exact Asymptotics of Linear Quadratic Adaptive Control and Population-level Comorbidity Analysis
(2022-12-22)
We present two self-contained topics in this thesis: exact asymptotics of linear quadratic adaptive control (LQAC) and population-level comorbidity analysis.
LQAC is perhaps the simplest non-bandit reinforcement learning ...
Discriminative Sequence Models Extract Personally Identifiable Information from Public Gene Expression Datasets
(2022-05-25)
The growing scale of functional genomics datasets is enabling researchers to better understand the genetic determinants of gene expression, for example through expression quantitative trait loci (eQTL) studies.
With an ...
Bayesian Statistical Framework for High-Dimensional Count Data and its Application in Microbiome Studies
(2017-05-10)
High-dimensional count data arising from multinomial sampling is ubiquitous in microbiome studies. This dissertation aims to develop flexible Bayesian framework to model high-dimensional count data, which provides reliable ...
Methods for the Analysis of Complex Time-to-Event Data
(2017-08-10)
This dissertation work is motivated by two time-to-event data examples, where current statistical methods are inadequate in addressing the nuances of data and the corresponding scientific question(s) of interest.
In Chapter ...