I am a final year graduate student in the math department at Stanford University, co-advised by James Zou and Lexing Ying.

My primary research interest is machine learning. I am particularly interested in developing sound theory for data-centric AI.

During the summer of 2022, I was an intern at Google CAIR, hosted by Jinsung Yoon and Sercan Arik.

I can be reached at zizzo at stanford dot edu.


Publications

How to Learn when Data Gradually Reacts to Your Model
Zachary Izzo, James Zou, Lexing Ying
International Conference on AI and Statistics (AISTATS 2022)

Dimensionality Reduction for Wasserstein Barycenter
Zachary Izzo, Sandeep Silwal, Samson Zhou
Conference on Neural Information Processing Systems (NeurIPS 2021)

How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
International Conference on Machine Learning (ICML 2021)

Borrowing From the Future: Addressing Double Sampling in Model-free Control
Yuhua Zhu, Zachary Izzo, Lexing Ying
Mathematical and Scientific Machine Learning (MSML 2021)

Approximate Data Deletion from Machine Learning Models
Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou
International Conference on AI and Statistics (AISTATS 2021)


Preprints/Workshop Papers

Provable Re-Identification Privacy
Zachary Izzo, Jinsung Yoon, Sercan Arik, James Zou
Under review

Data-Driven Subgroup Identification for Linear Regression
Zachary Izzo, Ruishan Liu, James Zou
Under review

Importance Tempering: Group Robustness for Overparameterized Models
Yiping Lu, Wenlong Ji, Zachary Izzo, Lexing Ying
Under review

Stateful Performative Gradient Descent
Zachary Izzo, James Zou, Lexing Ying
Socially Responsible Machine Learning (ICML SRML 2021)