I am currently a Ph.D student in the Machine Learning Program at the School of Mathematics, Georgia Tech. My research interests lie in the theory and application of machine learning, variational inference and high-dimensional statistics.
Before joining Gerogia Tech, I obtained my MS degree in Statistics at the University of Chicago, under the supervision of Lek-Heng Lim and Alexander Strang. I received my bachelor's degrees from the School of EECS and the School of Mathematical Science at Peking University.
Yucong Liu
yucongliu@gatech.edu
School of Mathematics
Georgia Institute of Technology
686 Cherry Street
Atlanta
USA
Publications
Published Articles- Zilai Si, Yucong Liu, Alexander Strang Path-following methods for Maximum a Posteriori estimators in Bayesian hierarchical models SIAM Journal on Optimization
- Yucong Liu Neural Networks are Integrable International Conference on Scientific Computing and Machine Learning 2024 [Oral]
- Yucong Liu, Simiao Jiao, Lek-Heng Lim LU decomposition and Toeplitz decomposition of a neural network Applied and Computational Harmonic Analysis
- Yucong Liu, Shixing Yu, Tong Lin Hessian regularization of deep neural networks: A novel approach based on stochastic estimators of Hessian trace Neurocomputing
- Hanwen Xu, Jiayou Zhang, Zhirui Wang, Shizhuo Zhang, Megh Bhalerao, Yucong Liu, Dawei Zhu, Sheng Wang GraphPrompt: Graph-Based Prompt Templates for Biomedical Synonym Prediction AAAI 2023
- Zehua Lai, Lek-Heng Lim, Yucong Liu Attention is a smoothed cubic spline
- Yucong Liu, Chi-Hua Wang, Guang Cheng On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation
Reading List
"Once again I had to put myself in a vulnerable position in order to become stronger." ― Cédric Villani, Birth of a Theorem: A Mathematical Adventure