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Alumni

Visit Stanford University Libraries to search for the PhD dissertations of our graduates.

Graduation Year
Student
Dissertation
Advisor
Committee Members

Principal Component Analysis Under Extreme Aspect Ratios

Donoho

Johnstone, Montanari

Three Essays in Causal Inference

Rothenhaeusler

Owen, Romano

Estimation and Testing Methods for Causal Inference with Interference

Imbens (Econ) / Ugander (MSE)

Owen

Learning with Neural Networks in High Dimensions

Montanari

Donoho, Johnstone

On Some Topics in Statistical Learning: Cluster-Aware Lasso & Others

Tibshirani

Hastie, Palacios

Stability of Solutions of Random Optimization Problems Under Small Perturbations

Chatterjee

Dembo, Diaconis

Applications of Cooperative Game Theory to Interpretable Machine Learning

Owen

Palacios, Taylor

Permutation-Based Inference in Time Series Analysis

Romano

Duchi, Owen

Causal Inference with Non-standard Experimental Designs

Wager (GSB)

Hastie, Siegmund

Information-Theoretic and Computational Perspectives

Montanari

Johnstone, Schramm

Inference for Prediction Error Beyond the IID Assumption

Tibshirani

Hastie, Owen

Change-point Detection in Mean or Variance or Both

Siegmund

Lai, Linderman

Some applications of graph limits in probability and statistics

Chatterjee

Montanari, Dembo

Some probabilistic aspects of Yang-Mills

Chatterjee

Diaconis, Dembo

Confident and reliable statistical predictions in changing environments

Duchi

Candes, Liang (CS)

Applications of Machine Learning to Some Statistical Inference Problems

Hastie

Tibshirani, Wager

Scalable Inference for Crossed Random Effects Models

Owen/Hastie

Hastie, Linderman, Athey (GSB)

Reliability and stability in statistical and machine learning problems

Duchi

Candes, Donoho, Rothenhaeusler

Nonparametric perspectives on empirical Bayes

Wager (GSB)

Candes, Tibshirani

A Neural Network with Feature Sparsity

Tibshirani

Duchi, Hastie

Causal and Selective Inference in Complex Statistical Models

Candes/Wager (GSB)

Hastie

Likelihood ratio testing in critically-spiked Wigner models

Johnstone

Owen, Dembo

Topics in multiple hypothesis testing and robustification of estimators through causal inference methods

Zou (BDS)

Candes, Owen

Phase Transitions of Disordered Systems and High Dimensional Inference

Dembo

Chatterjee, Montanari

Advances in multivariate statistics and its applications

Hastie

Tibshirani, Segal (UCSF)

Applied Statistical Methods for High-Dimensional Generalized Linear Models

Candes

Montanari, Taylor

Mallows permutation model: Sampling algorithms and probabilistic properties

Diaconis

Dembo, Siegmund

Topics in Exact Asymptotics for High-dimensional Regression

Montanari

Candes, Donoho

Minimax Regret Bounds for Stochastic Linear Bandit Algorithms

Bayati (GSB)

Lai, Candes

Model-Free Methods for Multiple Testing and Predictive Inference

Candes

Tibshirani, Owen

Advances in Contextual Multi-armed Bandits, Dynamic Treatment Strategies, and Type 1 Error Rate Guarantees in Confirmatory Adaptive Multi-arm Clinical Trials

Lai

Lavori (BDS), Lu (BDS), Palacios

Extending the Reach of the Lasso and Elastic Net Penalties: Methodology and Practice

Tibshirani

Art Owen, Guenther Walther

A Nonparametric Measure of Conditional Dependence

Chatterjee

Taylor, Bayati (GSB)

Causal Inference in Genetic Trio Studies

Candes

Tibshirani, Wager

Statistics and Uncertainty Quantification in Graphs and Networks with Biomedical Applications

Holmes

Friedman, Leskovec (CS)

Topics in Machine Learning for Causal Inference with Applications in Social Science

Athey (Econ)

Owen, Hastie

Statistical methods for adaptive data analysis

Taylor

Tibshirani, Romano

The Algebra and Machine Representation of Statistical Models

Candes

Hastie, Chambers, Musen (Med/BDS)

Large-scale and High-dimensional Statistical Learning: Methods and Algorithms

Hastie

Tibshirani, Rivas (BDS)

Making Causal Conclusions from Heterogeneous Data Sources

Owen/Baiocchi

Palacios

New Methods for Variable Importance Testing with Applications to Genetic Studies

Candes

Sabatti, Tibshirani

Sampling Methods for Perfect Bipartite Matchings

Diaconis

Chatterjee, Charikar (CS)

Asymptotic Theory for Large Random Matrices and its Applications

Dembo

Chatterjee, Montanari

Boosting Like Path Algorithms for L1 Regularized Infinite Dimensional Convex Neural Networks

Hastie

Taylor, Tibshirani

When do gradient methods work well in non-convex learning problems?

Duchi

Montanari, Candes

Topics in Selective Inference and its Application to Instrumental Variables

Taylor

Tibshirani, Lai

Modern Statistical Approaches for Randomized Experiments Under Interference

Ugander (MSE)

Walther, Palacios

Some hierarchical and group regularization methods and applications

Tibshirani

Taylor, Imbens (GSB)

Classification and testing under robust model assumptions

Tibshirani/Wong

Efron

Multiple Testing with Structure and Exploration

Sabatti

Candes, Montanari