Ziquan Liu
About
Hi, I am Ziquan Liu, a 5th year PhD student of computer science at City University of Hong Kong in Video, Image, and Sound Analysis Lab. My research interest is machine learning, including of deep learning and its mathematical interpretation, statistical learning and efficient training and inference. I was born and raised in Anhui province of China. I obtained my Bachelor of Engineering in Information Engineering from Beihang University and secondary Bachelor of Science in Mathematics from the same university, both in 2017.
Contact
Email: ziquanliu2-c@my.cityu.edu.hk
Address: Run Run Shaw Creative Media Center M5001, 18 Tat Hong Avenue, Kowloon, Hong Kong
News
[June 22, 2021]
I will join Alibaba DAMO Academy as a research intern and work with Dr. Yi Xu!
[Mar 12, 2021]
PRIMAL-GMM code is available at https://github.com/ziquanliu/PRIMAL-GMM!
Preprints
[1] Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Xiangyang Ji, Antoni B. Chan, "An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation." arXiv preprint, arXiv: 2205.12753, 2022.
[2] Ziquan Liu, Yufei Cui, Jia Wan, Yu Mao, Antoni B. Chan, "Weight Rescaling: Effective and Robust Regularization for Deep Neural Networks with Batch Normalization" arXiv preprint, arXiv:2102.03497, 2022.
Publications
[1] Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni B. Chan, Rong Jin, "Improved Fine-Tuning by Better Leveraging Pre-Training Data" Neural Information Processing Systems (NeurIPS), 2022
[2] Ziquan Liu, Lei Yu, Janet H. Hsiao and Antoni B. Chan, "PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models." IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
[3] Ziquan Liu, Yufei Cui, Antoni B. Chan, "Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations." ICML Workshop on Adversarial Machine Learning, 2021
[5] Jia Wan, Ziquan Liu, and Antoni B. Chan, "A Generalized Loss Function for Crowd Counting and Localization", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[6] Yufei Cui, Ziquan Liu, Qiao Li, Yu Mao, Antoni B. Chan, Chun Jason Xue, "Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression." IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[7] Hui Lan, Ziquan Liu, Janet H. Hsiao, Dan Yu, Antoni B. Chan, "Clustering Hidden Markov Models with Variational Bayesian Hierarchical EM." IEEE Transactions on Neural Networks and Learning Systems, To Appear 2021
[8] Yufei Cui, Ziquan Liu, Wuguanguan Yao, Qiao Li, Antoni B. Chan, Tei-Wei Kuo, Chun Jason Xue. "Fully Nested Neural Network for Adaptive Compression and Quantization.", Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI), 2020
[9] Ziquan Liu, Lei Yu, Janet H. Hsiao and Antoni B. Chan. "Parametric Manifold Learning of Gaussian Mixture Models." Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI), 3073-3079, 2019
Teaching
Teaching Assistant at City University of Hong Kong:
CS5489 Machine Learning: Algorithms and Applications, 2019-2020, 2020-2021
CS5486 Intelligent Systems, 2019-2020, 2020-2021
Service
Reviewer:
NeurIPS 2021-2022, ICLR 2021-2023, ICML 2021-2022, AAAI 2021-2023, CVPR 2021-2022, ICCV 2021, ECCV 2022
Service Award:
Outstanding Reviewer: NeurIPS 2021