I am a first-year Ph.D. student in Computer Science and Engineering Department at University of California San Diego (UCSD). I’m fortunate to be advised by Prof. Tsui-Wei (Lily) Weng. I received my master of science degree from UCSD and bachelor of engineering degree from Xi’an Jiaotong University.
My current research interests are theoretical machine learning and its applications, with a focus on
- Deep learning theory (optimization, generalization, robustness)
- Reinforcement learning theory
On the Equivalence between Neural Network and Support Vector Machine. [code][slides][poster][video]
Yilan Chen, Wei Huang, Lam M. Nguyen, Tsui-Wei Weng.
Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021).
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).
Preprint & Under Review
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning.
Wei Huang*, Chunrui Liu*, Yilan Chen, Tianyu Liu, Richard Yi Da Xu.
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation.
Quanshi Zhang*, Xu Cheng*, Yilan Chen, Zhefan Rao.
In submission to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
- DSC 291 Trustworthy Machine Learning, Tutor, Fall 2021
- NeurIPS 2022, Reviewer
- ICML 2022, Reviewer
- ICLR 2022, Reviewer
University of California San Diego, La Jolla, CA
Email: yilanchen6 [at] gmail.com