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Xinyi Chen

xinyic@princeton.edu

I am a Ph.D. candidate in the Department of Computer Science at Princeton University, where I am very fortunate to be advised by Prof. Elad Hazan. Concurrently, I am a research scientist at Google DeepMind. Previously, I completed my undergraduate studies also at Princeton, in the Mathematics Department. I was generously funded by the NSF Graduate Research Fellowship and the Gordon Wu Fellowship from Princeton University.

My research is at the intersection of machine learning, optimization, and dynamical systems. I focus on developing provably robust and efficient methods for sequential decision-making and control, with applications in deep learning and medical devices.

Preprints

Publications

Conference Publications

Preference Learning Algorithms Do Not Learn Preference Rankings.
Angelica Chen, Sadhika Malladi, Lily H Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho
NeurIPS 2024.
Adaptive Regret for Bandits Made Possible: Two Queries Suffice.
Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David Woodruff, Elad Hazan
ICLR 2024.
Online Control for Meta-optimization.
Xinyi Chen and Elad Hazan
NeurIPS 2023. Spotlight
Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions.
Vladimir Feinberg, Xinyi Chen, Y. Jennifer Sun, Rohan Anil, Elad Hazan
NeurIPS 2023.
Provable Regret Bounds for Deep Online Learning and Control.
Xinyi Chen, Edgar Minasyan, Jason D. Lee, Elad Hazan
L4DC 2023.
Adaptive Online Learning of Quantum States.
Xinyi Chen, Elad Hazan, Tongyang Li, Zhou Lu, Xinzhao Wang, Rui Yang
QIP 2023.
Robust Online Control with Model Misspecification.
Udaya Ghai, Xinyi Chen, Elad Hazan, Alexandre Megretski
L4DC 2022.
Machine Learning for Mechanical Ventilation Control.
Daniel Suo, Naman Agarwal, Wenhan Xia, Xinyi Chen, Udaya Ghai, Alexander Yu, Paula Gradu, Karan Singh, Cyril Zhang, Edgar Minasyan, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel Cohen, Elad Hazan
ML4H 2021. Extended Abstract
Black-Box Control for Linear Dynamical Systems.
Xinyi Chen and Elad Hazan
COLT 2021.
Online Agnostic Boosting via Regret Minimization.
Nataly Brukhim, Xinyi Chen, Elad Hazan, Shay Moran
NeurIPS 2020.
Calibration, Entropy Rates, and Memory in Language Models.
Mark Braverman, Xinyi Chen, Sham M. Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang
ICML 2020.
Extreme Tensoring for Low-Memory Preconditioning.
Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang
ICLR 2020.
Efficient Full-Matrix Adaptive Regularization. Tensorflow Optimizer
Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang
ICLR 2020.
Online Learning of Quantum States.
Scott Aaronson, Xinyi Chen, Elad Hazan, Satyen Kale, Ashwin Nayak
NeurIPS 2018 and QIP 2019.

Workshops

Onling Agnostic Boosting. Women in Machine Learning Workshop 2019. Oral Presentation.
With Nataly Brukhim, Elad Hazan, Shay Moran.

Journal Proceedings

Online Learning of Quantum States.
Scott Aaronson, Xinyi Chen, Elad Hazan, Satyen Kale, Ashwin Nayak
Journal of Statistical Mechanics: Theory and Experiment, 2019.
Adaptive Online Learning of Quantum States.
Xinyi Chen, Elad Hazan, Tongyang Li, Zhou Lu, Xinzhao Wang, Rui Yang
Quantum, 2024.

Service

Area Chair: NeurIPS 2023, 2024
Program Committee: COLT 2021-24
General Co-Chair: Women in Machine Learning (WiML) Workshop 2020
Reviewer: NeurIPS (2020-22), ICML (2020-24), L4DC, AISTATS, JMLR, TMLR, ALC, ICLR

Talks

Provable Regret Bounds for Deep Online Learning and Control.
- Google Research Learning Theory Workshop, Virtual. October 2021.
Black-Box Control for Linear Dynamical Systems.
- Google Research Diff-everything Workshop, Virtual. September 2021.
- Conference on Learning Theory, Boulder, CO, USA. August 2021.
- RL Theory Virtual Seminars, November 2020.
Online Agnostic Boosting via Regret Minimization.
- Google Research Conference, Mountain View, CA, USA. February 2020.
- MSR New England ML Lunch, Boston, MA, USA. January 2020.
- WiML, Vancouver, BC, Canada. December 2019.
Efficient Full-Matrix Adaptive Regularization.
- International Conference on Machine Learning, Long Beach, CA, USA. June 2019.
Online Learning of Quantum States.
- Princeton Algorithm and Machine Learning Seminar, Princeton, NJ, USA. September 2018.