Jiashuo Liu

According to our database, Jiashuo Liu authored at least 39 papers between 2016 and 2024.

Collaborative distances:

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

2024

Robust Bipartite Output Regulation of Linear Uncertain Multi-Agent Systems Under Observer-Based Protocols.

Jiashuo Liu, Cui-Qin Ma, Yun-Bo Zhao, Yu Kang

IEEE Trans. Circuits Syst. II Express Briefs, January, 2024

Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph.

Weihuang Zheng, Jiashuo Liu, Jiaxing Li, Jiayun Wu, Peng Cui, Youyong Kong

CoRR, 2024

Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift.

Jiayun Wu, Jiashuo Liu, Peng Cui, Zhiwei Steven Wu

CoRR, 2024

Stability Evaluation via Distributional Perturbation Analysis.

Jose H. Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu

CoRR, 2024

A Survey on Evaluation of Out-of-Distribution Generalization.

Han Yu, Jiashuo Liu, Xingxuan Zhang, Jiayun Wu, Peng Cui

CoRR, 2024

Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models.

Didi Zhu, Zexi Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications.

Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui

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

Stability Evaluation through Distributional Perturbation Analysis.

José H. Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu

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

Domain-wise Data Acquisition to Improve Performance under Distribution Shift.

Yue He, Dongbai Li, Pengfei Tian, Han Yu, Jiashuo Liu, Hao Zou, Peng Cui

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

Towards Robust Out-of-Distribution Generalization Bounds via Sharpness.

Yingtian Zou, Kenji Kawaguchi, Yingnan Liu, Jiashuo Liu, Mong-Li Lee, Wynne Hsu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Distributionally Generative Augmentation for Fair Facial Attribute Classification.

Fengda Zhang, Qianpei He, Kun Kuang, Jiashuo Liu, Long Chen, Chao Wu, Jun Xiao, Hanwang Zhang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Rethinking the Evaluation Protocol of Domain Generalization.

Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Enhancing Distributional Stability among Sub-populations.

Jiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng, Bo Li, Peng Cui

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

A deep learning aided differential distinguisher improvement framework with more lightweight and universality.

Jiashuo Liu, Jiongjiong Ren, Shaozhen Chen

Cybersecur., December, 2023

Distributionally Robust Learning With Stable Adversarial Training.

Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li

IEEE Trans. Knowl. Data Eng., November, 2023

Improved neural distinguishers with multi-round and multi-splicing construction.

Jiashuo Liu, Jiongjiong Ren, Shaozhen Chen, ManMan Li

J. Inf. Secur. Appl., May, 2023

VIS Atlas: A Database of Virus Integration Sites in Human Genome from NGS Data to Explore Integration Patterns.

Ye Chen, Yuyan Wang, Ping Zhou, Hao Huang, Rui Li, Zhen Zeng, Zifeng Cui, Rui Tian, Zhuang Jin, Jiashuo Liu, Zhaoyue Huang, Lifang Li, Zheying Huang, Xun Tian, Meiying Yu, Zheng Hu

Genom. Proteom. Bioinform., April, 2023

Bridging the Gap: Neural Collapse Inspired Prompt Tuning for Generalization under Class Imbalance.

Didi Zhu, Yinchuan Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Zexi Li, Kun Kuang, Chao Wu

CoRR, 2023

Meta Adaptive Task Sampling for Few-Domain Generalization.

Zheyan Shen, Han Yu, Peng Cui, Jiashuo Liu, Xingxuan Zhang, Linjun Zhou, Furui Liu

CoRR, 2023

Exploring and Exploiting Data Heterogeneity in Recommendation.

Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, Peng Cui

CoRR, 2023

Predictive Heterogeneity: Measures and Applications.

Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui

CoRR, 2023

Offline Policy Evaluation in Large Action Spaces via Outcome-Oriented Action Grouping.

Jie Peng, Hao Zou, Jiashuo Liu, Shaoming Li, Yibao Jiang, Jian Pei, Peng Cui

Proceedings of the ACM Web Conference 2023, 2023

On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets.

Jiashuo Liu, Tianyu Wang, Peng Cui, Hongseok Namkoong

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

Measure the Predictive Heterogeneity.

Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, Peng Cui

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Triple Generative Adversarial Networks.

Chongxuan Li, Kun Xu, Jun Zhu, Jiashuo Liu, Bo Zhang

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

Effective Network Parameter Reduction Schemes for Neural Distinguisher.

Jiashuo Liu, Jiongjiong Ren, Shaozhen Chen

IACR Cryptol. ePrint Arch., 2022

Distributionally Invariant Learning: Rationalization and Practical Algorithms.

Jiashuo Liu, Jiayun Wu, Jie Peng, Zheyan Shen, Bo Li, Peng Cui

CoRR, 2022

Towards Domain Generalization in Object Detection.

Xingxuan Zhang, Zekai Xu, Renzhe Xu, Jiashuo Liu, Peng Cui, Weitao Wan, Chong Sun, Chen Li

CoRR, 2022

Distributionally Robust Optimization with Data Geometry.

Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui

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

Invariant Preference Learning for General Debiasing in Recommendation.

Zimu Wang, Yue He, Jiashuo Liu, Wenchao Zou, Philip S. Yu, Peng Cui

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Towards Out-Of-Distribution Generalization: A Survey.

Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui

CoRR, 2021

Kernelized Heterogeneous Risk Minimization.

Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Signed Graph Neural Network with Latent Groups.

Haoxin Liu, Ziwei Zhang, Peng Cui, Yafeng Zhang, Qiang Cui, Jiashuo Liu, Wenwu Zhu

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Heterogeneous Risk Minimization.

Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen

Proceedings of the 38th International Conference on Machine Learning, 2021

Stable Adversarial Learning under Distributional Shifts.

Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Invariant Adversarial Learning for Distributional Robustness.

Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin

CoRR, 2020

Stable Learning via Differentiated Variable Decorrelation.

Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2016

Novel 3D-WPP algorithms for parallel HEVC encoding.

Ziyu Wen, Bichuan Quo, Jiashuo Liu, Jisheng Li, Yao Lu, Jiangtao Wen

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Intra Frame Flicker Reduction for Parallelized HEVC Encoding.

Ziyu Wen, Jisheng Li, Jiashuo Liu, Yikai Zhao, Jiangtao Wen

Proceedings of the 2016 Data Compression Conference, 2016