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Haotao Wang
Haotao Wang
Qualcomm
Verified email at utexas.edu - Homepage
Title
Cited by
Cited by
Year
Model compression with adversarial robustness: A unified optimization framework
S Gui, H Wang, H Yang, C Yu, Z Wang, J Liu
NeurIPS 2019, 1285-1296, 2019
1572019
Autogan-distiller: Searching to compress generative adversarial networks
Y Fu, W Chen, H Wang, H Li, Y Lin, Z Wang
ICML 2020, 2020
1002020
Triple wins: Boosting accuracy, robustness and efficiency together by enabling input-adaptive inference
TK Hu, T Chen, H Wang, Z Wang
ICLR 2020, 2020
922020
AugMax: Adversarial Composition of Random Augmentations for Robust Training
H Wang, C Xiao, J Kossaifi, Z Yu, A Anandkumar, Z Wang
Advances in Neural Information Processing Systems 34, 2021
902021
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free
H Wang, T Chen, S Gui, TK Hu, J Liu, Z Wang
NeurIPS 2020, 2020
75*2020
Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset
Z Wu, H Wang, Z Wang, Z Wang, H Jin
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
73*2020
GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework
H Wang, S Gui, H Yang, J Liu, Z Wang
ECCV 2020, 2020
602020
Taxonomy of machine learning safety: A survey and primer
S Mohseni, H Wang, C Xiao, Z Yu, Z Wang, J Yadawa
ACM Computing Surveys 55 (8), 1-38, 2022
40*2022
Efficient split-mix federated learning for on-demand and in-situ customization
J Hong, H Wang, Z Wang, J Zhou
International Conference on Learning Representations, 2022
382022
Partial and asymmetric contrastive learning for out-of-distribution detection in long-tailed recognition
H Wang, A Zhang, Y Zhu, S Zheng, M Li, AJ Smola, Z Wang
International Conference on Machine Learning, 23446-23458, 2022
372022
Removing batch normalization boosts adversarial training
H Wang, A Zhang, S Zheng, X Shi, M Li, Z Wang
International Conference on Machine Learning, 23433-23445, 2022
342022
Federated robustness propagation: Sharing adversarial robustness in federated learning
J Hong, H Wang, Z Wang, J Zhou
Proceedings of the AAAI Conference on Artificial Intelligence 2023 1, 2021
272021
I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively
H Wang, T Chen, Z Wang, K Ma
ICLR 2020, 2020
212020
Troubleshooting Blind Image Quality Models in the Wild
Z Wang, H Wang, T Chen, Z Wang, K Ma
CVPR 2021, 2021
172021
Real-time rogue ONU identification with 1D-CNN-based optical spectrum analysis for secure PON
Y Li, N Hua, C Zhao, H Wang, R Luo, X Zheng
2019 Optical Fiber Communications Conference and Exhibition (OFC), 1-3, 2019
112019
Learning model-based privacy protection under budget constraints
J Hong, H Wang, Z Wang, J Zhou
Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 7702-7710, 2021
102021
How robust is your fairness? evaluating and sustaining fairness under unseen distribution shifts
H Wang, J Hong, J Zhou, Z Wang
Transactions on machine learning research 2023, 2023
82023
Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork
H Wang, J Hong, A Zhang, J Zhou, Z Wang
NeurIPS 2022, 2022
82022
Troubleshooting image segmentation models with human-in-the-loop
H Wang, T Chen, Z Wang, K Ma
Machine Learning 112 (3), 1033-1051, 2023
4*2023
UMEC: Unified model and embedding compression for efficient recommendation systems
J Shen, H Wang, S Gui, J Tan, Z Wang, J Liu
International Conference on Learning Representations, 2020
42020
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