预印本论文
会议论文
Understanding incremental learning of gradient descent: A fine-grained analysis of matrix sensing
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound
Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning
(按字母序排序)
Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate
Single-Source Bottleneck Path Algorithm Faster than Sorting for Sparse Graphs
(按字母序排序)
(默认按贡献排序;星号 * 表示贡献相同)
- 普林斯顿大学 2024 年春季学期. Teaching Assistant for COS324: Introduction to Machine Learning (taught by Prof. Sanjeev Arora & Prof. Elad Hazan).
- 普林斯顿大学 2022 年秋季学期. Teaching Assistant for COS521: Advanced Algorithm Design (taught by Prof. Matt Weinberg & Prof. Huacheng Yu).
- 普林斯顿大学 2021 年春季学期. Teaching Assistant for COS598B: Advanced Topics in Computer Science: Mathematical Understanding of Deep Learning (taught by Prof. Sanjeev Arora).
- 清华大学 2020 年春季学期. 计算机应用数学 助教(授课教师:姚期智教授).
- 清华大学 2019 年春季学期. 分布式计算:基础与系统 助教(授课教师:陈卫