Xie, Yue, Jiawen Bi, and Hongcheng Liu. "Stochastic First-Order Methods with Non-smooth and Non-Euclidean Proximal Terms for Nonconvex High-Dimensional Stochastic Optimization." Major revision with Mathematical Programming. Online as arXiv preprint arXiv:2406.19475 (2024).
Liu, Hongcheng, and Jindong Tong. "New Sample Complexity Bounds for Sample Average Approximation in Heavy-Tailed Stochastic Programming." In Forty-first International Conference on Machine Learning (2024)
Liu, Hongcheng, and Jindong Tong. "Metric Entropy-Free Sample Complexity Bounds for Sample Average Approximation in Convex Stochastic Programming." arXiv:2401.00664 (2024)
Liu, Hongcheng, Yinyu Ye, and Hung Yi Lee. "High-dimensional learning under approximate sparsity with applications to nonsmooth estimation and regularized neural networks." Operations Research 70, no. 6 (2022): 3176-3197.
Chen, Yunmei, Hongcheng Liu, Xiaojing Ye, and Qingchao Zhang. "Learnable descent algorithm for nonsmooth nonconvex image reconstruction." SIAM Journal on Imaging Sciences 14, no. 4 (2021): 1532-1564.
Liu, H., Wang, X., Yao, T., Li, R. and Ye, Y., 2019. Sample average approximation with sparsity-inducing penalty for high-dimensional stochastic programming. Mathematical programming, 178, pp.69-108.
Haeser, G., Liu, H. and Ye, Y., 2019. Optimality condition and complexity analysis for linearly-constrained optimization without differentiability on the boundary. Mathematical Programming, 178(1), pp.263-299.
Liu, H., Yao, T., Li, R. and Ye, Y., 2017. Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions. Mathematical programming, 166(1), pp.207-240.
Liu, Hongcheng, Tao Yao, and Runze Li. "Global solutions to folded concave penalized nonconvex learning." Annals of statistics 44, no. 2 (2016): 629.
Hernandez, Charles, Bijan Taslimi, Hung Yi Lee, Hongcheng Liu, and Panos M. Pardalos. "Training generalizable quantized deep neural nets." Expert Systems with Applications 213 (2023): 118736.
Cai, Hongwei, Zheng Ao, Chunhui Tian, Zhuhao Wu, Hongcheng Liu, Jason Tchieu, Mingxia Gu, Ken Mackie, and Feng Guo. "Brain organoid reservoir computing for artificial intelligence." Nature Electronics 6, no. 12 (2023): 1032-1039.
Ao, Zheng, Hongwei Cai, Zhuhao Wu, Liya Hu, Asael Nunez, Zhuolong Zhou, Hongcheng Liu et al. "Microfluidics guided by deep learning for cancer immunotherapy screening." Proceedings of the National Academy of Sciences 119, no. 46 (2022): e2214569119.
Han, Dong, Jingdong Tong, Yu Yang, Hongcheng Liu, Xiaoying Liang, Sridhar Yaddanapudi, Chunjoo Park et al. "Optimizing spot intensity with lower bound constraints for IMPT: Exposing shortcomings and introducing an enhanced strategy." Medical Physics (2024).
Tseng, Wenchih, Hongcheng Liu, Yu Yang, Chihray Liu, and Bo Lu. "An ultra-fast deep-learning-based dose engine for prostate VMAT via knowledge distillation framework with limited patient data." Physics in Medicine & Biology 68, no. 1 (2022): 015002.
Taslimi, Bijan, Farnaz Babaie Sarijaloo, Hongcheng Liu, and Panos M. Pardalos. "A novel mixed integer programming model for freight train travel time estimation." European Journal of Operational Research 300, no. 2 (2022): 676-688.
Han, Ke, Terry L. Friesz, W. Y. Szeto, and Hongcheng Liu. "Elastic demand dynamic network user equilibrium: Formulation, existence and computation." Transportation Research Part B: Methodological 81 (2015): 183-209.
Han, Ke, Hongcheng Liu, Vikash V. Gayah, Terry L. Friesz, and Tao Yao. "A robust optimization approach for dynamic traffic signal control with emission considerations." Transportation Research Part C: Emerging Technologies 70 (2016): 3-26.
Liu, Hongcheng, Ke Han, Vikash V. Gayah, Terry L. Friesz, and Tao Yao. "Data-driven linear decision rule approach for distributionally robust optimization of on-line signal control." Transportation Research Part C: Emerging Technologies 59 (2015): 260-277.
Wang, Yiou, Hongcheng Liu, Ke Han, Terry L. Friesz, and Tao Yao. "Day-to-day congestion pricing and network resilience." Transportmetrica A: Transport Science 11, no. 9 (2015): 873-895.
Han, Ke, Yuqi Sun, Hongcheng Liu, Terry L. Friesz, and Tao Yao. "A bi-level model of dynamic traffic signal control with continuum approximation." Transportation Research Part C: Emerging Technologies 55 (2015): 409-431.