Liu, Mingyan

21 publications

NeurIPS 2025 Learning Expandable and Adaptable Representations for Continual Learning Ruilong Yu, Mingyan Liu, Fei Ye, Adrian G. Bors, Rongyao Hu, Jingling Sun, Shijie Zhou

ICLR 2024 Fair Classifiers That Abstain Without Harm Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu

TMLR 2024 Federated Learning with Reduced Information Leakage and Computation Tongxin Yin, Xuwei Tan, Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu

AAAI 2024 Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts Kun Jin, Tongxin Yin, Zhongzhu Chen, Zeyu Sun, Xueru Zhang, Yang Liu, Mingyan Liu

ICLR 2023 DensePure: Understanding Diffusion Models for Adversarial Robustness Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song

NeurIPS 2023 Long-Term Fairness with Unknown Dynamics Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu

ICLRW 2023 Long-Term Fairness with Unknown Dynamics Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu

ICLRW 2023 Performative Federated Learning Kun Jin, Tongxin Yin, Zhongzhu Chen, Zeyu Sun, Xueru Zhang, Yang Liu, Mingyan Liu

NeurIPSW 2022 DensePure: Understanding Diffusion Models Towards Adversarial Robustness Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song

ICML 2022 Fairness Interventions as (Dis)Incentives for Strategic Manipulation Xueru Zhang, Mohammad Mahdi Khalili, Kun Jin, Parinaz Naghizadeh, Mingyan Liu

ICCV 2021 Can Shape Structure Features Improve Model Robustness Under Diverse Adversarial Settings? Mingjie Sun, Zichao Li, Chaowei Xiao, Haonan Qiu, Bhavya Kailkhura, Mingyan Liu, Bo Li

AAAI 2021 Multi-Scale Games: Representing and Solving Games on Networks with Group Structure Kun Jin, Yevgeniy Vorobeychik, Mingyan Liu

NeurIPS 2020 How Do Fair Decisions Fare in Long-Term Qualification? Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellstrom, Kun Zhang, Cheng Zhang

NeurIPS 2020 Robust Deep Reinforcement Learning Against Adversarial Perturbations on State Observations Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Mingyan Liu, Duane Boning, Cho-Jui Hsieh

NeurIPS 2019 Group Retention When Using Machine Learning in Sequential Decision Making: The Interplay Between User Dynamics and Fairness Xueru Zhang, Mohammadmahdi Khaliligarekani, Cem Tekin, Mingyan Liu

ECCV 2018 Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation Chaowei Xiao, Ruizhi Deng, Bo Li, Fisher Yu, Mingyan Liu, Dawn Song

IJCAI 2018 Generating Adversarial Examples with Adversarial Networks Chaowei Xiao, Bo Li, Jun-Yan Zhu, Warren He, Mingyan Liu, Dawn Song

ICML 2018 Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu

ICLR 2018 Spatially Transformed Adversarial Examples Chaowei Xiao, Jun-Yan Zhu, Bo Li, Warren He, Mingyan Liu, Dawn Song

IJCAI 2017 Crowd Learning: Improving Online Decision Making Using Crowdsourced Data Yang Liu, Mingyan Liu

AAAI 2016 Finding One's Best Crowd: Online Learning by Exploiting Source Similarity Yang Liu, Mingyan Liu