Model Compression with Adversarial Robustness: A Unified Optimization Framework. - Shupeng Gui; Haotao Wang; Haichuan Yang; Chen Yu 009; Zhangyang Wang; Ji Liu 002 (NeurIPS, 2019)

Real-Time Rogue ONU Identification with 1D-CNN-Based Optical Spectrum Analysis for Secure PON. - Yanlong Li 002; Nan Hua; Chen Zhao; Haotao Wang; Ruijie Luo; Xiaoping Zheng (OFC, 2019)

Adversarially Trained Model Compression: When Robustness Meets Efficiency. - Shupeng Gui; Haotao Wang; Chen Yu 009; Haichuan Yang; Zhangyang Wang; Ji Liu 002 (CoRR, 2019)

Privacy-Preserving Deep Visual Recognition: An Adversarial Learning Framework and A New Dataset. - Haotao Wang; Zhenyu Wu 002; Zhangyang Wang; Zhaowen Wang; Hailin Jin (CoRR, 2019)

GAN Slimming: All-in-One GAN Compression by a Unified Optimization Framework. - Haotao Wang; Shupeng Gui; Haichuan Yang; Ji Liu 002; Zhangyang Wang (ECCV (4), 2020)

Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference. - Ting-Kuei Hu; Tianlong Chen 001; Haotao Wang; Zhangyang Wang (ICLR, 2020)

I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively. - Haotao Wang; Tianlong Chen 001; Zhangyang Wang; Kede Ma (ICLR, 2020)

AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks. - Yonggan Fu; Wuyang Chen 001; Haotao Wang; Haoran Li; Yingyan Lin; Zhangyang Wang (ICML, 2020)

Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free. - Haotao Wang; Tianlong Chen 001; Shupeng Gui; Ting-Kuei Hu; Ji Liu 002; Zhangyang Wang (NeurIPS, 2020)

Learning Model-Based Privacy Protection under Budget Constraints. - Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (AAAI, 2021)

Troubleshooting Blind Image Quality Models in the Wild. - Zhihua Wang 002; Haotao Wang; Tianlong Chen 001; Zhangyang Wang; Kede Ma (CVPR, 2021)

UMEC: Unified model and embedding compression for efficient recommendation systems. - Jiayi Shen; Haotao Wang; Shupeng Gui; Jianchao Tan; Zhangyang Wang; Ji Liu 002 (ICLR, 2021)

AugMax: Adversarial Composition of Random Augmentations for Robust Training. - Haotao Wang; Chaowei Xiao; Jean Kossaifi; Zhiding Yu; Anima Anandkumar; Zhangyang Wang (NeurIPS, 2021)

Practical Machine Learning Safety: A Survey and Primer. - Sina Mohseni; Haotao Wang; Zhiding Yu; Chaowei Xiao; Zhangyang Wang; Jay Yadawa (CoRR, 2021)

Federated Robustness Propagation: Sharing Adversarial Robustness in Federated Learning. - Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (CoRR, 2021)

AutoMARS: Searching to Compress Multi-Modality Recommendation Systems. - Duc Hoang; Haotao Wang; Handong Zhao; Ryan A. Rossi; Sungchul Kim; Kanak Mahadik; Zhangyang Wang (CIKM, 2022)

Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization. - Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (ICLR, 2022)

Removing Batch Normalization Boosts Adversarial Training. - Haotao Wang; Aston Zhang; Shuai Zheng 004; Xingjian Shi; Mu Li 003; Zhangyang Wang (ICML, 2022)

Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition. - Haotao Wang; Aston Zhang; Yi Zhu 001; Shuai Zheng 004; Mu Li 003; Alex J. Smola; Zhangyang Wang (ICML, 2022)

Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork. - Haotao Wang; Junyuan Hong; Aston Zhang; Jiayu Zhou; Zhangyang Wang (NeurIPS, 2022)

Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset. - Zhenyu Wu 002; Haotao Wang; Zhaowen Wang; Hailin Jin; Zhangyang Wang (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning. - Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (AAAI, 2023)

Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection. - Shuyang Yu; Junyuan Hong; Haotao Wang; Zhangyang Wang; Jiayu Zhou (ICLR, 2023)

Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. - Haotao Wang; Ziyu Jiang; Yuning You; Yan Han 001; Gaowen Liu; Jayanth Srinivasa; Ramana Kompella; Zhangyang Wang (NeurIPS, 2023)

Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. - Haotao Wang; Ziyu Jiang; Yan Han 001; Zhangyang Wang (CoRR, 2023)

Taxonomy of Machine Learning Safety: A Survey and Primer. - Sina Mohseni; Haotao Wang; Chaowei Xiao; Zhiding Yu; Zhangyang Wang; Jay Yadawa (ACM Comput. Surv., 2023)

How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts. - Haotao Wang; Junyuan Hong; Jiayu Zhou; Zhangyang Wang (Trans. Mach. Learn. Res., 2023)

Troubleshooting image segmentation models with human-in-the-loop. - Haotao Wang; Tianlong Chen 001; Zhangyang Wang; Kede Ma (Mach. Learn., 2023)

Safe and Robust Watermark Injection with a Single OoD Image. - Shuyang Yu; Junyuan Hong; Haobo Zhang 002; Haotao Wang; Zhangyang Wang; Jiayu Zhou (ICLR, 2024)