Ziquan Liu

According to our database, Ziquan Liu authored at least 34 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization.

Zhaohan Zhang, Ziquan Liu, Ioannis Patras

Proceedings of the 31st International Conference on Computational Linguistics, 2025

Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions.

Reem I. Masoud, Ziquan Liu, Martin Ferianc, Philip C. Treleaven, Miguel Rodrigues

Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024

Borrowing Treasures from Neighbors: In-Context Learning for Multimodal Learning with Missing Modalities and Data Scarcity.

Zhuo Zhi, Ziquan Liu, Moe Elbadawi, Adam Daneshmend, Mine Orlu, Abdul Basit, Andreas Demosthenous, Miguel Rodrigues

CoRR, 2024

PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks.

Ziquan Liu, Zhuo Zhi, Ilija Bogunovic, Carsten Gerner-Beuerle, Miguel Rodrigues

CoRR, 2024

A gender recognition method based on EEG microstates.

Yanxiang Niu, Xin Chen, Yuansen Chen, Zixuan Yao, Xuemei Chen, Ziquan Liu, Xiangyan Meng, Yanqing Liu, Zongya Zhao, Haojun Fan

Comput. Biol. Medicine, 2024

The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks.

Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, Antoni B. Chan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key Networks.

Feiyu Chen, Wei Lin, Ziquan Liu, Antoni B. Chan

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Analysing educational scientific collaboration through multilayer networks: patterns, impact and network generation model.

Shenwen Chen, Yisen Wang, Ziquan Liu, Wenbo Du, Lei Zheng, Runran Liu

J. Complex Networks, September, 2023

Variational Nested Dropout.

Yufei Cui, Yu Mao, Ziquan Liu, Qiao Li, Antoni B. Chan, Xue (Steve) Liu, Tei-Wei Kuo, Chun Jason Xue

IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

Clustering Hidden Markov Models With Variational Bayesian Hierarchical EM.

Hui Lan, Ziquan Liu, Janet H. Hsiao, Dan Yu, Antoni B. Chan

IEEE Trans. Neural Networks Learn. Syst., March, 2023

Retrieval-Augmented Multiple Instance Learning.

Yufei Cui, Ziquan Liu, Yixin Chen, Yuchen Lu, Xinyue Yu, Xue (Steve) Liu, Tei-Wei Kuo, Miguel Rodrigues, Chun Jason Xue, Antoni B. Chan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bayes-MIL: A New Probabilistic Perspective on Attention-based Multiple Instance Learning for Whole Slide Images.

Yufei Cui, Ziquan Liu, Xiangyu Liu, Xue Liu, Cong Wang, Tei-Wei Kuo, Chun Jason Xue, Antoni B. Chan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks.

Qiangqiang Wu, Tianyu Yang, Ziquan Liu, Baoyuan Wu, Ying Shan, Antoni B. Chan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization.

Ziquan Liu, Yi Xu, Xiangyang Ji, Antoni B. Chan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models.

Ziquan Liu, Lei Yu, Janet H. Hsiao, Antoni B. Chan

IEEE Trans. Pattern Anal. Mach. Intell., 2022

An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation.

Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Rong Jin, Xiangyang Ji, Antoni B. Chan

CoRR, 2022

Improved Fine-Tuning by Better Leveraging Pre-Training Data.

Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni B. Chan, Rong Jin

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization.

Ziquan Liu, Antoni B. Chan

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Clustering Hidden Markov Models with Variational Bayesian Hierarchical EM.

Hui Lan, Ziquan Liu, Janet H. Hsiao, Dan Yu, Antoni B. Chan

Dataset, January, 2021

Improved Fine-tuning by Leveraging Pre-training Data: Theory and Practice.

Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Antoni B. Chan, Rong Jin

CoRR, 2021

The Implicit Biases of Stochastic Gradient Descent on Deep Neural Networks with Batch Normalization.

Ziquan Liu, Yufei Cui, Jia Wan, Yu Mao, Antoni B. Chan

CoRR, 2021

Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression.

Yufei Cui, Ziquan Liu, Qiao Li, Yu Mao, Antoni B. Chan, Chun Jason Xue

CoRR, 2021

Maintenance Decision Generator for Electrical Equipment Based on Reinforcement Learning.

Ruifan Li, Zeyuan Wang, Yifan Du, Zepeng Zhai, Yongping Xiong, Ziquan Liu

Proceedings of the SPML 2021: 4th International Conference on Signal Processing and Machine Learning, Beijing, China, August 18, 2021

A Deep Image Denoising Method at Transmit Electricity Surveillance Environment.

Nan Yao, Ziquan Liu, Zhen Wang, Yongling Lu, Jianhua Qin

Proceedings of the 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, 2021

Target Detection of Engineering Vehicles Based on Co-learning Labels.

Zhen Wang, Nan Yao, Ziquan Liu, Xueqiong Zhu, Hai Xue

Proceedings of the 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, 2021

Bolt Defect Detection Based on CenterNet Model.

Nan Yao, Yuxi Zhao, Xi Wu, Ziquan Liu, Jianhua Qin

Proceedings of the IEEE Intl Conf on Dependable, 2021

Detection of Transmission Line Corridors Risk Intrusion based on B-CNN.

Nan Yao, Ziquan Liu, Zhen Wang, Yongling Lu, Hai Xue

Proceedings of the IEEE Intl Conf on Dependable, 2021

Feature Pyramid Hierarchy based DeltaNet Network for Insulator Defect Detection.

Ziquan Liu, Nan Yao, Xi Wu, Jinggang Yang, Hai Xue

Proceedings of the IEEE Intl Conf on Dependable, 2021

A Generalized Loss Function for Crowd Counting and Localization.

Jia Wan, Ziquan Liu, Antoni B. Chan

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression.

Yufei Cui, Ziquan Liu, Qiao Li, Antoni B. Chan, Chun Jason Xue

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations.

Ziquan Liu, Yufei Cui, Antoni B. Chan

CoRR, 2020

Fully Nested Neural Network for Adaptive Compression and Quantization.

Yufei Cui, Ziquan Liu, Wuguannan Yao, Qiao Li, Antoni B. Chan, Tei-Wei Kuo, Chun Jason Xue

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Parametric Manifold Learning of Gaussian Mixture Models.

Ziquan Liu, Lei Yu, Janet H. Hsiao, Antoni B. Chan

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2017

Optimization of Spectrum-Energy Efficiency in Heterogeneous Communication Network.

Fangqing Gu, Ziquan Liu, Yiu-ming Cheung, Hai-Lin Liu

Proceedings of the Simulated Evolution and Learning - 11th International Conference, 2017