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1. Differentially Private Convex Optimization For Empirical Risk Minimization And High-dimensional Regression

open_access
Open Access
Author:
Guha Thakurta, Abhradeep
Title:
Differentially Private Convex Optimization For Empirical Risk Minimization And High-dimensional Regression
Graduate Program:
Computer Science and Engineering
Keywords:
Data Privacy
Differential Privacy
Machine Learning
High-dimensional Statistics
Sparse Regression
File:
Download AbhradeepThakurta-Dissertation.pdf
Committee Members:
Adam Davison Smith, Dissertation Advisor/Co-Advisor
Adam Davison Smith, Committee Chair/Co-Chair
Daniel Kifer, Committee Member
Aleksandra B Slavkovic, Committee Member
Sofya Raskhodnikova, Committee Member

2. Computational Advantages in High Dimensions

open_access
Open Access
Author:
White, Stephen
Title:
Computational Advantages in High Dimensions
Graduate Program:
Mathematics
Keywords:
Probability
Sparse Recovery
Restricted Isometry Property
Phase Retrieval
Dictionary Learning
Metagenomics
Inverse Problems
High-dimensional Statistics
File:
Download StephenWhite_Dissertation_Revised.pdf
Committee Members:
Pierre-Emmanuel Jabin, Program Head/Chair
Anna Mazzucato, Major Field Member
Pierre-Emmanuel Jabin, Major Field Member
Alexei Novikov, Chair & Dissertation Advisor
Bharath Kumar Sriperumbudur, Outside Unit, Field & Minor Member