Dr Fanghui Liu

Research Interests:

  • Machine learning 
  • Kernel methods
  • Learning Theory

 

Biography

Dr Fanghui Liu is currently an Assistant Professor at the University of Warwick, UK. He received the B.E. degree in Automation from Harbin Institute of Technology, China, and the Ph.D. degree from Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, China, in 2014 and 2019, respectively. Before joining in LIONS Lab in October 2021 in EPFL, he worked as a postdoc researcher in ESAT-STADIUS, KU Leuven, Belgium from Oct. 2019 to Sep. 2021. His research areas mainly include machine learning, kernel methods, and learning theory.

Robust NAS under adversarial training: benchmark, theory, and beyond

Y. Wu; F. Liu; C-J. Simon-Gabriel; G. Chrysos; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

Y. Chen; F. Liu; T. Suzuki; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Y. Chen; F. Liu; Y. Lu; G. Chrysos; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

Revisiting Character-level Adversarial Attacks for Language Models

E. Abad Rocamora; Y. Wu; F. Liu; G. Chrysos; V. Cevher 

2024. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024.

Efficient local linearity regularization to overcome catastrophic overfitting

E. Abad Rocamora; F. Liu; G. Chrysos; P. M. Olmos; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

Contact

e-mail address: [email protected]


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