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Some interesting figures

Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks

Published in arXiv Preprint, 2020

We make several new observations about the top eigenspace of layer-wise Hessians and explained the phenomena using Kronecker factorization. The insights also led to better explicit generalization bounds for neural nets.

Recommended citation: Wu, Y., Zhu, X., Wu, C., Wang, A. and Ge, R., 2020. Dissecting hessian: Understanding common structure of hessian in neural networks. arXiv preprint arXiv:2010.04261. https://arxiv.org/abs/2010.04261

Understanding Edge-of-Stability Training Dynamics with a Minimalist Example

Published in arXiv Preprint, 2022

We conduct rigorous convergence analysis on a 2D model exhibiting both sharpness concentration and sharpness adaptivity phenomena.

Recommended citation: Zhu X., Wang Z., Wang, X., Zhou, M. and Ge, R., 2022. Understanding Edge-of-Stability Training Dynamics with a Minimalist Example. arXiv preprint arXiv:2210.03294. https://arxiv.org/abs/2210.03294

Fairness in the Assignment Problem with Uncertain Priorities

Published in arXiv Preprint, 2023

We proposed two new notions of fairness when there exists uncertainty in the piorities. We also proposed two algorithms with certain guarantees of the proposed notion of fairness.

Recommended citation: Shen, Z., Wang, Z., Zhu, X., Fain, B., & Munagala, K. (2023). Fairness in the Assignment Problem with Uncertain Priorities. arXiv preprint arXiv:2301.13804. https://arxiv.org/abs/2301.13804

Undergraduate TA for CS230 (Discrete Math for Computer Science)

Undergraduate course, Duke University, Department of Computer Science, 2022

Responsible for leading recitations, holding office hours, and grading.

Undergraduate TA for CS330 (Design & Analysis of Algorithms)

Undergraduate course, Duke University, Department of Computer Science, 2022

Responsible for holding office hours and grading.

Undergraduate TA for CS330 (Design & Analysis of Algorithms)

Undergraduate course, Duke University, Department of Computer Science, 2022

Responsible for leading recitations and grading.

Graduate TA for COS 324 (Introduction to Machine Learning)

Undergraduate course, Princeton University, Department of Computer Science, 2024

Responsible for teaching precepts, developing assignments and exam questions, and holding office hours.