I am a seconed-year master student in Computer Science and Engineering Department at University of California San Diego working with Prof. Tsui-Wei (Lily) Weng and Dr. Lam M. Nguyen. I received my Bachelor of Engineering Degree from Xi’an Jiaotong University. Here is my CV. I am looking for a Ph.D. position starting from 2022.
I am interested in theoretical machine learning and its applications, especially
- Deep learning theory (optimization, generalization, robustness)
- Reinforcement learning theory
- Problems motivated by practical applications
On the Equivalence between Neural Network and Support Vector Machine. (slides)
Yilan Chen, Wei Huang, Lam M. Nguyen, Tsui-Wei Weng.
Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021).
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation.
Quanshi Zhang$^\ast$, Xu Cheng$^\ast$, Yilan Chen, Zhefan Rao.
In submission to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
Explaining Knowledge Distillation by Quantifying the Knowledge.
Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020).
- DSC 291 Trustworthy Machine Learning, Tutor, Fall 2021
- Machine Learning:
- CSE 250A Probabilistic Reason & Learning A+
- CSE 251A ML: Learning Algorithms A+
- CSE 251C ML: Machine Learning Theory A
- CSE 252A Computer Vision I A+
- CSE 257 Search and Optimization A
- MATH 245A Convex Analysis & Optimization I A
- MATH 245B Convex Analysis & Optimization II A
- ECE 269 Linear Algebra and Application A
- MATH 281A Mathematical Statistics ongoing
- ICLR 2022, Reviewer