Capture expression-dependent AU relations for expression recognition. - Jun Wang 130; Shangfei Wang; Mengdi Huai; Chongliang Wu; Zhen Gao 003; Yue Liu; Qiang Ji (ICME Workshops, 2014)

Efficient Privacy-Preserving Aggregation for Mobile Crowdsensing. - Mengdi Huai; Liusheng Huang; Yu-e Sun; Wei Yang 011 (BDCloud, 2015)

Privacy-Preserving Naive Bayes Classification. - Mengdi Huai; Liusheng Huang; Wei Yang 011; Lu Li; Mingyu Qi (KSEM, 2015)

Personalized disease prediction using a CNN-based similarity learning method. - Qiuling Suo; Fenglong Ma; Ye Yuan 006; Mengdi Huai; Weida Zhong; Aidong Zhang; Jing Gao 004 (BIBM, 2017)

Differentially Private Sparse Inverse Covariance Estimation. - Di Wang 015; Mengdi Huai; Jinhui Xu 001 (GlobalSIP, 2018)

Multi-task Sparse Metric Learning for Monitoring Patient Similarity Progression. - Qiuling Suo; Weida Zhong; Fenglong Ma; Ye Yuan 006; Mengdi Huai; Aidong Zhang (ICDM, 2018)

Metric Learning from Probabilistic Labels. - Mengdi Huai; Chenglin Miao; Yaliang Li; Qiuling Suo; Lu Su 001; Aidong Zhang (KDD, 2018)

Towards Data Poisoning Attacks in Crowd Sensing Systems. - Chenglin Miao; Qi Li 012; Houping Xiao; Wenjun Jiang; Mengdi Huai; Lu Su 001 (MobiHoc, 2018)

Representation Learning for Treatment Effect Estimation from Observational Data. - Liuyi Yao; Sheng Li 001; Yaliang Li; Mengdi Huai; Jing Gao 004; Aidong Zhang (NeurIPS, 2018)

Uncorrelated Patient Similarity Learning. - Mengdi Huai; Chenglin Miao; Qiuling Suo; Yaliang Li; Jing Gao 004; Aidong Zhang (SDM, 2018)

Attack under Disguise: An Intelligent Data Poisoning Attack Mechanism in Crowdsourcing. - Chenglin Miao; Qi Li 012; Lu Su 001; Mengdi Huai; Wenjun Jiang; Jing Gao 004 (WWW, 2018)

ACE: Adaptively Similarity-Preserved Representation Learning for Individual Treatment Effect Estimation. - Liuyi Yao; Sheng Li 001; Yaliang Li; Mengdi Huai; Jing Gao 004; Aidong Zhang (ICDM, 2019)

Privacy-aware Synthesizing for Crowdsourced Data. - Mengdi Huai; Di Wang 015; Chenglin Miao; Jinhui Xu 001; Aidong Zhang (IJCAI, 2019)

Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm. - Mengdi Huai; Hongfei Xue; Chenglin Miao; Liuyi Yao; Lu Su 001; Changyou Chen; Aidong Zhang (IJCAI, 2019)

DTEC: Distance Transformation Based Early Time Series Classification. - Liuyi Yao; Yaliang Li; Yezheng Li; Hengtong Zhang; Mengdi Huai; Jing Gao 004; Aidong Zhang (SDM, 2019)

Pairwise Learning with Differential Privacy Guarantees. - Mengdi Huai; Di Wang 015; Chenglin Miao; Jinhui Xu 001; Aidong Zhang (AAAI, 2020)

Towards Interpretation of Pairwise Learning. - Mengdi Huai; Di Wang 015; Chenglin Miao; Aidong Zhang (AAAI, 2020)

EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks. - Jinduo Liu 001; Junzhong Ji; Guangxu Xun; Liuyi Yao; Mengdi Huai; Aidong Zhang (AAAI, 2020)

Analysis of Meta-Learning Approaches for TCGA Pan-cancer Datasets. - Jingyuan Chou; Stefan Bekiranov; Chongzhi Zang; Mengdi Huai; Aidong Zhang (BIBM, 2020)

Global Interpretation for Patient Similarity Learning. - Mengdi Huai; Chenglin Miao; Jinduo Liu 001; Di Wang 015; Jingyuan Chou; Aidong Zhang (BIBM, 2020)

Malicious Attacks against Deep Reinforcement Learning Interpretations. - Mengdi Huai; Jianhui Sun; Renqin Cai; Liuyi Yao; Aidong Zhang (KDD, 2020)

Learning Distance Metrics from Probabilistic Information. - Mengdi Huai; Chenglin Miao; Yaliang Li; Qiuling Suo; Lu Su 001; Aidong Zhang (ACM Trans. Knowl. Discov. Data, 2020)

SCI: Subspace Learning Based Counterfactual Inference for Individual Treatment Effect Estimation. - Liuyi Yao; Yaliang Li; Sheng Li 001; Mengdi Huai; Jing Gao 004; Aidong Zhang (CIKM, 2021)

Differentially Private Pairwise Learning Revisited. - Zhiyu Xue; Shaoyang Yang; Mengdi Huai; Di Wang 015 (IJCAI, 2021)

Adversarial Attacks against LiDAR Semantic Segmentation in Autonomous Driving. - Yi Zhu 012; Chenglin Miao; Foad Hajiaghajani; Mengdi Huai; Lu Su 001; Chunming Qiao (SenSys, 2021)

Towards Automating Model Explanations with Certified Robustness Guarantees. - Mengdi Huai; Jinduo Liu 001; Chenglin Miao; Liuyi Yao; Aidong Zhang (AAAI, 2022)

Brain Effective Connectivity Learning with Deep Reinforcement Learning. - Yilin Lu; Jinduo Liu 001; Junzhong Ji; Han Lv; Mengdi Huai (BIBM, 2022)

Patient Similarity Learning with Selective Forgetting. - Wei Qian; Chenxu Zhao; Huajie Shao; Minghan Chen; Fei Wang 001; Mengdi Huai (BIBM, 2022)

Demystify Hyperparameters for Stochastic Optimization with Transferable Representations. - Jianhui Sun; Mengdi Huai; Kishlay Jha; Aidong Zhang (KDD, 2022)

On the Robustness of Metric Learning: An Adversarial Perspective. - Mengdi Huai; Tianhang Zheng; Chenglin Miao; Liuyi Yao; Aidong Zhang (ACM Trans. Knowl. Discov. Data, 2022)

SEAT: Stable and Explainable Attention. - Lijie Hu; Yixin Liu 002; Ninghao Liu; Mengdi Huai; Lichao Sun 001; Di Wang 015 (AAAI, 2023)

Understanding and Enhancing Robustness of Concept-Based Models. - Sanchit Sinha; Mengdi Huai; Jianhui Sun; Aidong Zhang (AAAI, 2023)

Towards Understanding and Enhancing Robustness of Deep Learning Models against Malicious Unlearning Attacks. - Wei Qian; Chenxu Zhao; Wei Le; Meiyi Ma; Mengdi Huai (KDD, 2023)

Static and Sequential Malicious Attacks in the Context of Selective Forgetting. - Chenxu Zhao; Wei Qian; Rex Ying; Mengdi Huai (NeurIPS, 2023)

Learning to Learn Task Transformations for Improved Few-Shot Classification. - Guangtao Zheng; Qiuling Suo; Mengdi Huai; Aidong Zhang (SDM, 2023)

Inductive Graph Unlearning. - Cheng-Long Wang 003; Mengdi Huai; Di Wang 015 (USENIX Security Symposium, 2023)

Path-specific Causal Fair Prediction via Auxiliary Graph Structure Learning. - Liuyi Yao; Yaliang Li; Bolin Ding; Jingren Zhou 001; Jinduo Liu 001; Mengdi Huai; Jing Gao 004 (WWW, 2023)

Automated Natural Language Explanation of Deep Visual Neurons with Large Models. - Chenxu Zhao; Wei Qian; Yucheng Shi; Mengdi Huai; Ninghao Liu (CoRR, 2023)

Improving Faithfulness for Vision Transformers. - Lijie Hu; Yixin Liu 002; Ninghao Liu; Mengdi Huai; Lichao Sun 001; Di Wang 015 (CoRR, 2023)

Concept-Level Model Interpretation From the Causal Aspect. - Liuyi Yao; Yaliang Li; Sheng Li 001; Jinduo Liu 001; Mengdi Huai; Aidong Zhang; Jing Gao 004 (IEEE Trans. Knowl. Data Eng., 2023)

Fostering Trustworthiness in Machine Learning Algorithms. - Mengdi Huai (AAAI, 2024)

Backdoor Attacks via Machine Unlearning. - Zihao Liu; Tianhao Wang 001; Mengdi Huai; Chenglin Miao (AAAI, 2024)

Towards Modeling Uncertainties of Self-Explaining Neural Networks via Conformal Prediction. - Wei Qian; Chenxu Zhao; Yangyi Li; Fenglong Ma; Chao Zhang 014; Mengdi Huai (AAAI, 2024)

Automated Natural Language Explanation of Deep Visual Neurons with Large Models (Student Abstract). - Chenxu Zhao; Wei Qian; Yucheng Shi; Mengdi Huai; Ninghao Liu (AAAI, 2024)

AdvST: Revisiting Data Augmentations for Single Domain Generalization. - Guangtao Zheng; Mengdi Huai; Aidong Zhang (AAAI, 2024)

Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning. - Jiaqi Wang 002; Chenxu Zhao; Lingjuan Lyu; Quanzeng You; Mengdi Huai; Fenglong Ma (ICML, 2024)

Improving Interpretation Faithfulness for Vision Transformers. - Lijie Hu; Yixin Liu 002; Ninghao Liu; Mengdi Huai; Lichao Sun 001; Di Wang 015 (ICML, 2024)

Data Poisoning Attacks against Conformal Prediction. - Yangyi Li; Aobo Chen; Wei Qian; Chenxu Zhao; Divya Lidder; Mengdi Huai (ICML, 2024)

Rethinking Adversarial Robustness in the Context of the Right to be Forgotten. - Chenxu Zhao; Wei Qian; Yangyi Li; Aobo Chen; Mengdi Huai (ICML, 2024)

Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models. - Yuan Zhong 002; Xiaochen Wang 002; Jiaqi Wang 002; Xiaokun Zhang 001; Yaqing Wang 001; Mengdi Huai; Cao Xiao; Fenglong Ma (KDD, 2024)

Modeling and Understanding Uncertainty in Medical Image Classification. - Aobo Chen; Yangyi Li; Wei Qian; Kathy Morse; Chenglin Miao; Mengdi Huai (MICCAI (10), 2024)

MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation. - Yuan Zhong 002; Suhan Cui; Jiaqi Wang 002; Xiaochen Wang 002; Ziyi Yin 003; Yaqing Wang 001; Houping Xiao; Mengdi Huai; Ting Wang 006; Fenglong Ma (SDM, 2024)

Exploring Fairness in Educational Data Mining in the Context of the Right to be Forgotten. - Wei Qian; Aobo Chen; Chenxu Zhao; Yangyi Li; Mengdi Huai (CoRR, 2024)

Neuron Explanations for Conformal Prediction (Student Abstract). - Divya Lidder; Kathryn Morse; Bridget Sullivan; Wei Qian; Chenglin Miao; Mengdi Huai (AAAI, 2025)

A survey of security and privacy issues of machine unlearning. - Aobo Chen; Yangyi Li; Chenxu Zhao; Mengdi Huai (AI Mag., 2025)

White-box Membership Inference Attacks against Diffusion Models. - Yan Pang; Tianhao Wang 001; Xuhui Kang; Mengdi Huai; Yang Zhang 016 (Proc. Priv. Enhancing Technol., 2025)

Towards Stable and Explainable Attention Mechanisms. - Lijie Hu; Xinhai Wang; Yixin Liu 002; Ninghao Liu; Mengdi Huai; Lichao Sun 001; Di Wang 015 (IEEE Trans. Knowl. Data Eng., 2025)

Towards Unveiling Predictive Uncertainty Vulnerabilities in the Context of the Right to Be Forgotten. - Wei Qian; Chenxu Zhao; Yangyi Li; Wenqian Ye; Mengdi Huai (CoRR, 2025)