Qizhou WangPh.D. Student
TMLR Group
[Google Scholar]
[Github] |
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I am a fourth-year Ph.D. student at Trustworthy Machine Learning and Reasoning (TMLR) Group in the Department of Computer Science, Hong Kong Baptist University, advised by Dr. Bo Han. I have worked as a visiting research student at RIKEN AIP, collaborating with Prof. Masashi Sugiyama and Dr. Gang Niu. I also work closely with Dr. Feng Liu and Dr. Zhen Fang.
My research interests lie in the broad areas of robust and reliable machine learning, including OOD Detection, adversarial robustness, and label noise robustness. Currently, I am studying unlearning and fine-tuning problems for foundation models.
@inproceedings{wang2024clips,
title={A Sober Look at the Robustness of CLIPs to Spurious Features},
author={Wang, Qizhou and Lin, Yong and Chen, Yongqiang and Schmidt, Ludwig and Han, Bo and Zhang, Tong},
booktitle={Advances in Neural Information Processing Systems},
year={2024},
}
@inproceedings{wang2023learning,
title={Learning to Augment Distributions for Out-of-distribution Detection},
author={Qizhou Wang and Zhen Fang and Yonggang Zhang and Feng Liu and Yixuan Li and Bo Han},
booktitle={Advances in Neural Information Processing Systems},
year={2023},
}
@inproceedings{zheng2023unreliable,
title={Out-of-distribution Detection with Unreliable Out-of-distribution Sources},
author={Haotian Zheng and Qizhou Wang and Zhen Fang and Xiaobo Xia and Feng Liu and Tongliang Liu and Bo Han},
booktitle={Advances in Neural Information Processing Systems},
year={2023},
}
@inproceedings{wang2023doe,
title={Out-of-distribution Detection with Implicit Outlier Transformation},
author={Qizhou Wang and Junjie Ye and Feng Liu and Quanyu Dai and Marcus Kalander and Tongliang Liu and Jianye Hao and Bo Han},
booktitle = {International Conference on Learning Representations},
year = {2023}
}
@inproceedings{wang2022watermark,
title={Watermarking for Out-of-distribution Detection},
author={Qizhou Wang and Feng Liu and Yonggang Zhang and Jing Zhang and Chen Gong and Tongliang Liu and Bo Han},
booktitle={Advances in Neural Information Processing Systems},
year={2022},
}
@inproceedings{sun2022towards,
title={Towards Lightweight Black-Box Attacks against Deep Neural Networks},
author={Chenghao Sun and Yonggang Zhang and Chaoqun Wan and Qizhou Wang and Ya Li and Tongliang Liu and Bo Han and Xinmei Tian},
booktitle={Advances in Neural Information Processing Systems},
year={2022},
}
@inproceedings{wang2021mail,
title={Probabilistic Margins for Instance Reweighting in Adversarial Training},
author={Qizhou Wang and Feng Liu and Bo Han and Tongliang Liu and Chen Gong and Gang Niu and Mingyuan Zhou and Masashi Sugiyama},
booktitle={NeurIPS},
year={2021}
}
@article{gong2021instance,
title={Instance-dependent positive and unlabeled learning with labeling bias estimation},
author={Gong, Chen and Wang, Qizhou and Liu, Tongliang and Han, Bo and You, Jane and Yang, Jian and Tao, Dacheng},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume={44},
number={8},
pages={4163--4177},
year={2021},
}
@inproceedings{wang2021tackling_instance,
title={Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model},
author={Qizhou Wang and Bo Han and Tongliang Liu and Gang Niu and Jian Yang and Chen Gong},
booktitle={AAAI},
year={2021}
}
@inproceedings{wang2021maxmatching,
title={Learning with Group Noise},
author={Qizhou Wang and Jiangchao Yao and Chen Gong and Tongliang Liu and Mingming Gong and Hongxia Yang and Bo Han},
booktitle={AAAI},
pages={10192--10200},
year={2021}
}
@inproceedings{zhang2021fraud,
title={Fraud detection under multi-sourced extremely noisy annotations},
author={Chuang Zhang and Qizhou Wang and Tengfei Liu and Xun Lu and Jin Hong and Bo Han and Chen Gong},
booktitle={CIKM},
year={2021}
}