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Jiashuo Liu
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2020 – today
- 2024
- [j6]Jiashuo Liu, Cui-Qin Ma, Yun-Bo Zhao, Yu Kang:
Robust Bipartite Output Regulation of Linear Uncertain Multi-Agent Systems Under Observer-Based Protocols. IEEE Trans. Circuits Syst. II Express Briefs 71(1): 340-344 (2024) - [c20]Jiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng, Bo Li, Peng Cui:
Enhancing Distributional Stability among Sub-populations. AISTATS 2024: 2125-2133 - [c19]Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui:
Rethinking the Evaluation Protocol of Domain Generalization. CVPR 2024: 21897-21908 - [c18]Fengda Zhang, Qianpei He, Kun Kuang, Jiashuo Liu, Long Chen, Chao Wu, Jun Xiao, Hanwang Zhang:
Distributionally Generative Augmentation for Fair Facial Attribute Classification. CVPR 2024: 22797-22808 - [c17]Yingtian Zou, Kenji Kawaguchi, Yingnan Liu, Jiashuo Liu, Mong-Li Lee, Wynne Hsu:
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness. ICLR 2024 - [c16]Yue He, Dongbai Li, Pengfei Tian, Han Yu, Jiashuo Liu, Hao Zou, Peng Cui:
Domain-wise Data Acquisition to Improve Performance under Distribution Shift. ICML 2024 - [c15]José H. Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu:
Stability Evaluation through Distributional Perturbation Analysis. ICML 2024 - [c14]Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui:
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications. ICML 2024 - [c13]Didi Zhu, Zexi Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu:
Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models. KDD 2024: 4631-4640 - [i23]Han Yu, Jiashuo Liu, Xingxuan Zhang, Jiayun Wu, Peng Cui:
A Survey on Evaluation of Out-of-Distribution Generalization. CoRR abs/2403.01874 (2024) - [i22]Yingtian Zou, Kenji Kawaguchi, Yingnan Liu, Jiashuo Liu, Mong-Li Lee, Wynne Hsu:
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness. CoRR abs/2403.06392 (2024) - [i21]Fengda Zhang, Qianpei He, Kun Kuang, Jiashuo Liu, Long Chen, Chao Wu, Jun Xiao, Hanwang Zhang:
Distributionally Generative Augmentation for Fair Facial Attribute Classification. CoRR abs/2403.06606 (2024) - [i20]Jose H. Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu:
Stability Evaluation via Distributional Perturbation Analysis. CoRR abs/2405.03198 (2024) - [i19]Jiayun Wu, Jiashuo Liu, Peng Cui, Zhiwei Steven Wu:
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift. CoRR abs/2406.00661 (2024) - [i18]Weihuang Zheng, Jiashuo Liu, Jiaxing Li, Jiayun Wu, Peng Cui, Youyong Kong:
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph. CoRR abs/2406.01066 (2024) - 2023
- [j5]Jiashuo Liu, Jiongjiong Ren, Shaozhen Chen:
A deep learning aided differential distinguisher improvement framework with more lightweight and universality. Cybersecur. 6(1): 47 (2023) - [j4]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:
VIS Atlas: A Database of Virus Integration Sites in Human Genome from NGS Data to Explore Integration Patterns. Genom. Proteom. Bioinform. 21(2): 300-310 (2023) - [j3]Jiashuo Liu, Jiongjiong Ren, Shaozhen Chen, ManMan Li:
Improved neural distinguishers with multi-round and multi-splicing construction. J. Inf. Secur. Appl. 74: 103461 (2023) - [j2]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li:
Distributionally Robust Learning With Stable Adversarial Training. IEEE Trans. Knowl. Data Eng. 35(11): 11288-11300 (2023) - [c12]Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, Peng Cui:
Measure the Predictive Heterogeneity. ICLR 2023 - [c11]Jiashuo Liu, Tianyu Wang, Peng Cui, Hongseok Namkoong:
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets. NeurIPS 2023 - [c10]Jie Peng, Hao Zou, Jiashuo Liu, Shaoming Li, Yibao Jiang, Jian Pei, Peng Cui:
Offline Policy Evaluation in Large Action Spaces via Outcome-Oriented Action Grouping. WWW 2023: 1220-1230 - [i17]Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui:
Predictive Heterogeneity: Measures and Applications. CoRR abs/2304.00305 (2023) - [i16]Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui:
Rethinking the Evaluation Protocol of Domain Generalization. CoRR abs/2305.15253 (2023) - [i15]Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, Peng Cui:
Exploring and Exploiting Data Heterogeneity in Recommendation. CoRR abs/2305.15431 (2023) - [i14]Zheyan Shen, Han Yu, Peng Cui, Jiashuo Liu, Xingxuan Zhang, Linjun Zhou, Furui Liu:
Meta Adaptive Task Sampling for Few-Domain Generalization. CoRR abs/2305.15644 (2023) - [i13]Didi Zhu, Yinchuan Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Zexi Li, Kun Kuang, Chao Wu:
Bridging the Gap: Neural Collapse Inspired Prompt Tuning for Generalization under Class Imbalance. CoRR abs/2306.15955 (2023) - [i12]Jiashuo Liu, Tianyu Wang, Peng Cui, Hongseok Namkoong:
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets. CoRR abs/2307.05284 (2023) - [i11]Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui:
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications. CoRR abs/2311.05054 (2023) - 2022
- [j1]Chongxuan Li, Kun Xu, Jun Zhu, Jiashuo Liu, Bo Zhang:
Triple Generative Adversarial Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9629-9640 (2022) - [c9]Zimu Wang, Yue He, Jiashuo Liu, Wenchao Zou, Philip S. Yu, Peng Cui:
Invariant Preference Learning for General Debiasing in Recommendation. KDD 2022: 1969-1978 - [c8]Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui:
Distributionally Robust Optimization with Data Geometry. NeurIPS 2022 - [i10]Xingxuan Zhang, Zekai Xu, Renzhe Xu, Jiashuo Liu, Peng Cui, Weitao Wan, Chong Sun, Chen Li:
Towards Domain Generalization in Object Detection. CoRR abs/2203.14387 (2022) - [i9]Jiashuo Liu, Jiayun Wu, Jie Peng, Zheyan Shen, Bo Li, Peng Cui:
Distributionally Invariant Learning: Rationalization and Practical Algorithms. CoRR abs/2206.02990 (2022) - [i8]Jiashuo Liu, Jiongjiong Ren, Shaozhen Chen, ManMan Li:
Improved Neural Distinguishers with Multi-Round and Multi-Splicing Construction. IACR Cryptol. ePrint Arch. 2022: 1279 (2022) - [i7]Jiashuo Liu, Jiongjiong Ren, Shaozhen Chen:
Effective Network Parameter Reduction Schemes for Neural Distinguisher. IACR Cryptol. ePrint Arch. 2022: 1765 (2022) - 2021
- [c7]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Stable Adversarial Learning under Distributional Shifts. AAAI 2021: 8662-8670 - [c6]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Heterogeneous Risk Minimization. ICML 2021: 6804-6814 - [c5]Haoxin Liu, Ziwei Zhang, Peng Cui, Yafeng Zhang, Qiang Cui, Jiashuo Liu, Wenwu Zhu:
Signed Graph Neural Network with Latent Groups. KDD 2021: 1066-1075 - [c4]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Kernelized Heterogeneous Risk Minimization. NeurIPS 2021: 21720-21731 - [i6]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Heterogeneous Risk Minimization. CoRR abs/2105.03818 (2021) - [i5]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li:
Distributionally Robust Learning with Stable Adversarial Training. CoRR abs/2106.15791 (2021) - [i4]Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui:
Towards Out-Of-Distribution Generalization: A Survey. CoRR abs/2108.13624 (2021) - [i3]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Kernelized Heterogeneous Risk Minimization. CoRR abs/2110.12425 (2021) - 2020
- [c3]Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen:
Stable Learning via Differentiated Variable Decorrelation. KDD 2020: 2185-2193 - [i2]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Invariant Adversarial Learning for Distributional Robustness. CoRR abs/2006.04414 (2020)
2010 – 2019
- 2019
- [i1]Chongxuan Li, Kun Xu, Jiashuo Liu, Jun Zhu, Bo Zhang:
Triple Generative Adversarial Networks. CoRR abs/1912.09784 (2019) - 2016
- [c2]Ziyu Wen, Jisheng Li, Jiashuo Liu, Yikai Zhao, Jiangtao Wen:
Intra Frame Flicker Reduction for Parallelized HEVC Encoding. DCC 2016: 111-120 - [c1]Ziyu Wen, Bichuan Quo, Jiashuo Liu, Jisheng Li, Yao Lu, Jiangtao Wen:
Novel 3D-WPP algorithms for parallel HEVC encoding. ICASSP 2016: 1471-1475
Coauthor Index
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