Experience

 
 
 
 
 

Research Intern

NVIDIA

May 2020 – Aug 2020 Santa Clara
 
 
 
 
 

Research Intern

Kwai Inc. Y-Lab

May 2019 – Aug 2019 Seattle

Publications

  • Haotao Wang*, Tianlong Chen*, Shupeng Gui, Ting-Kuei Hu, Ji Liu, and Zhangyang Wang. “Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free.” In Advances in Neural Information Processing Systems (NeurIPS), 2020. [pdf] [code]

  • Zhenyu Wu*, Haotao Wang*, Zhaowen Wang, Hailin Jin, and Zhangyang Wang. “Privacy-Preserving Deep Visual Recognition: An Adversarial Learning Framework and A New Dataset.” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
    * Equal contribution. [pdf] [project homepage] [code and dataset]

  • Haotao Wang, Shupeng Gui, Haichuan Yang, Ji Liu, and Zhangyang Wang. “GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework.” In European Conference on Computer Vision (ECCV), 2020. [Spotlight Oral] [pdf] [code]

  • Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, and Zhangyang Wang. “AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks.” In International Conference on Machine Learning (ICML), 2020.
    [pdf] [code]

  • Haotao Wang, Tianlong Chen, Zhangyang Wang, and Kede Ma. “I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively.” In International Conference on Learning Representations (ICLR), 2020.
    [pdf] [code]

  • Ting-Kuei Hu, Tianlong Chen, Haotao Wang, and Zhangyang Wang. “Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference.” In International Conference on Learning Representations (ICLR), 2020.
    [pdf] [code]

  • Shupeng Gui*, Haotao Wang*, Haichuan Yang, Chen Yu, Zhangyang Wang, and Ji Liu. “Model Compression with Adversarial Robustness: A Unified Optimization Framework.” In Advances in Neural Information Processing Systems (NeurIPS), 2019.
    * Equal contribution.
    [pdf] [code]