
Kaifeng Lyu 吕凯风
I am a final-year Ph.D. student in the Computer Science Department at Princeton University and I am very fortunate to be advised by Prof. Sanjeev Arora.
I did my undergraduate at Tsinghua University and received a B.Eng. in Computer Science and Technology in 2019. At Tsinghua, I was a student of Yao Class headed by Prof. Andrew Chi-Chih Yao and I was very fortunate to be advised by Prof. Jian Li.
News: I will be joining the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University as a Tenure-Track Assistant Professor in Fall 2025.
Conference Papers
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
(alphabetical order)
Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate
Single-Source Bottleneck Path Algorithm Faster than Sorting for Sparse Graphs
(alphabetical order)
(Contribution order by default; Asterisk * stands for equal contribution.)
- Fall 2022. Teaching Assistant for COS521: Advanced Algorithm Design (taught by Prof. Matt Weinberg & Prof. Huacheng Yu), Princeton University.
- Spring 2021. Teaching Assistant for COS598B: Advanced Topics in Computer Science: Mathematical Understanding of Deep Learning (taught by Prof. Sanjeev Arora), Princeton University.
- Spring 2020. Teaching Assistant for Mathematics for Computer Science (taught by Prof. Andrew Chi-Chih Yao), Tsinghua University.
- Spring 2019. Teaching Assistant for Distributed Computing (taught by Prof. Wei Chen), Tsinghua University.
Professional Services
- Conference Reviewer: ICML (2020-2023), NeurIPS (2020-2023), ICLR (2022,2023), TPAMI, COLT (2020), AAAI (2020), KDD (2022).
- Journal Reviewer: JMLR, TPAMI, AIJ.
- Organizer, Yao Class Seminar, Tsinghua University (Fall 2019, Fall 2020, Spring 2021).
Universal Online Judge
- I founded the Universal Online Judge (UOJ) in 2014, a popular online judge system in China.
- UOJ is capable of testing both traditional and non-traditional programming problems in OI (Olympiad in Informatics). A team of top OI players regularly hosts programming contests on UOJ.
- [Link] [GitHub] [Docs]