ZITONG YANG
I am a statistician at Stanford NLP group. I solve problems an AI engineer might care, in a way statisticians would prefer. I am jointly advised by Prof. Emmanuel Candès and Prof. Tatsunori Hashimoto. My research is generously supported by Albion Walter Hewlett Stanford Graduate Fellowship (SGF). Prior to Stanford, I spent some amazing years at Berkeley, working with Prof. Yi Ma and Prof. Jacob Steinhardt.
Education
- Ph.D. Statistics, Stanford University (2022-present)
- M.S. Electrical Engineering, University of California, Berkeley (2020-2021)
- B.A. Mathematics, Highest Honors, University of California, Berkeley (2016-2020)
- B.A. Computer Science, University of California, Berkeley (2016-2020)
- B.A. Physics, University of California, Berkeley (2016-2020)
Professional Experience
- Google Scholar
- Curriculum vitae
- Email: zitong@berkeley.edu
Publications
- Synthetic continued pretraining
Zitong Yang*, Neil Band*, Shuangping Li, Emmanuel Candès, Tatsunori Hashimoto
arXiv preprint, 2024. [code] [arXiv] [slides] [slides(Chinese)] - Bellman Conformal Inference: Calibrating Prediction Intervals For Time Series
Zitong Yang, Emmanuel Candès, Lihua Lei
arXiv preprint, 2024. [code] [arXiv] - ResMem: Learn what you can and memorize the rest
Zitong Yang, Michal Lukasik, Vaishnavh Nagarajan, Zonglin Li, Ankit Singh Rawat, Manzil Zaheer, Aditya Krishna Menon, Sanjiv Kumar
Neural Information Processing Systems (NeurIPS), 2023. [slides] [arXiv] - Predicting Out-of-Distribution Error with the Projection Norm
Yaodong Yu*, Zitong Yang*, Alexander Wei, Yi Ma, Jacob Steinhardt.
International Conference on Machine Learning (ICML), 2022. [slides] [arXiv] - Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models
Zitong Yang, Yu Bai, Song Mei.
International Conference on Machine Learning (ICML), 2021. [slides] [arXiv]
- Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition
Yaodong Yu*, Zitong Yang*, Edgar Dobriban, Jacob Steinhardt, Yi Ma.
arXiv preprint, 2021. [arXiv] - Rethinking the Bias-Variance Dilemma for Generalization of Neural Networks
Zitong Yang*, Yaodong Yu*, Chong You, Jacob Steinhardt, Yi Ma.
International Conference on Machine Learning (ICML), 2020. [slides] [arXiv] - Complete Dictionary Learning via l4- Maximization over the Orthogonal Group.
Yuexiang Zhai, Zitong Yang, Zhenyu Liao, John Wright, Yi Ma
Journal of Machine Learning Research (JMLR), 2020. [arXiv]