Yixuan's bio photo

Sharon Yixuan Li

Assistant Professor
Department of Computer Sciences
University of Wisconsin-Madison

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Publications and Preprints

You can also browse my Google Scholar profile. I publish under the name "Yixuan Li".

  • Xuefeng Du, Zhaoning Wang, Mu Cai, and Yixuan Li
    VOS: Learning What You Don’t Know by Virtual Outlier Synthesis
    In Proceedings of the 10th International Conference on Learning Representations (ICLR), 2022
    [BibTeX] [PDF] [Code]

      @article{du2022vos,
          title={VOS: Learning What You Don’t Know by Virtual Outlier Synthesis}, 
          author={Du, Xuefeng and Wang, Zhaoning and Cai, Mu and Li, Yixuan},
          journal={Proceedings of the International Conference on Learning Representations},
          year={2022}
    }
    
  • Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, and Junbo Zhao
    Contrastive Label Disambiguation for Partial Label Learning
    In Proceedings of the 10th International Conference on Learning Representations (ICLR), 2022
    [BibTeX] [PDF] [Code]

      @article{wang2022contrastive,
          title={Contrastive Label Disambiguation for Partial Label Learning}, 
          author={Wang, Haobo and Xiao, Ruixuan and Li, Yixuan and Feng, Lei and Niu, Gang and Chen, Gang and Zhao, Junbo},
          journal={Proceedings of the International Conference on Learning Representations},
          year={2022}
    }
    
  • Peyman Morteza and Yixuan Li
    Provable Guarantees for Understanding Out-of-distribution Detection
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022
    Acceptance Ratio: 15%
    [BibTeX] [PDF] [Code]

      @article{morteza2022provable,
          title={Provable Guarantees for Understanding Out-of-distribution Detection}, 
          author={Morteza, Peyman and Li, Yixuan},
          journal={Proceedings of the AAAI Conference on Artificial Intelligence},
          year={2022}
    }
    
  • Yifei Ming, Hang Yin and Yixuan Li
    On the Impact of Spurious Correlation for Out-of-distribution Detection
    Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2022
    Acceptance Ratio: 15%
    [BibTeX] [PDF] [Code]

      @article{ming2022spurious,
          title={On the Impact of Spurious Correlation for Out-of-distribution Detection}, 
          author={Ming, Yifei and Yin, Hang and Li, Yixuan},
          journal={Proceedings of the AAAI Conference on Artificial Intelligence},
          year={2022}
    }
    
  • Yiyou Sun, Chuan Guo and Yixuan Li
    ReAct: Out-of-distribution Detection With Rectified Activations
    Neural Information Processing Systems (NeurIPS), 2021
    [BibTeX] [PDF] [Code]

    @inproceedings{sun2021react,
      title={ReAct: Out-of-distribution Detection With Rectified Activations},
      author={Sun, Yiyou and Guo, Chuan and Li, Yixuan},
      booktitle={Advances in Neural Information Processing Systems},
      year={2021}
    }
    
  • Haoran Wang*, Weitang Liu, Alex Bocchieri and Yixuan Li*
    Can multi-label classification networks know what they don’t know?
    Neural Information Processing Systems (NeurIPS), 2021
    * indicates equal contribution
    [BibTeX] [PDF] [Code]

    @article{wang2021canmulti,
          title={Can multi-label classification networks know what they don't know?},
          author={Wang, Haoran and Liu, Weitang and Bocchieri, Alex and Li, Yixuan},
          journal={Advances in Neural Information Processing Systems},
          year={2021}
     }
    
  • Rui Huang, Andrew Geng and Yixuan Li
    On the Importance of Gradients for Detecting Distributional Shifts in the Wild
    Neural Information Processing Systems (NeurIPS), 2021
    [BibTeX] [PDF] [Code]

    @inproceedings{huang2021importance,
      title={On the Importance of Gradients for Detecting Distributional Shifts in the Wild},
      author={Huang, Rui and Geng, Andrew and Li, Yixuan},
      booktitle={Advances in Neural Information Processing Systems},
      year={2021}
    }
    
  • Jingkang Yang, Kaiyang Zhou, Yixuan Li, and Ziwei Liu
    Generalized Out-of-Distribution Detection: A Survey
    Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
    [BibTeX] [PDF] [Code]

    @article{yang2021generalized,
      title={Generalized Out-of-Distribution Detection: A Survey},
      author={Yang, Jingkang and Zhou, Kaiyang and Li, Yixuan and Liu, Ziwei},
      journal={arXiv preprint arXiv:2110.11334},
      year={2021}
    }
    
  • Yiyou Sun and Yixuan Li
    On the Effectiveness of Sparsification for Detecting the Deep Unknowns
    Preprints, 2021
    [BibTeX] [PDF] [Code]

      @article{sun2021effectiveness,
          title={On the Effectiveness of Sparsification for Detecting the Deep Unknowns}, 
          author={Sun, Yiyou and Li, Yixuan},
          journal={arXiv preprint arXiv:2111.09805},
          year={2021}
    }
    
  • Mohammadreza Salehi, Hossein Mirzaei, Dan Hendrycks, Yixuan Li, Mohammad Hossein Rohban, Mohammad Sabokrou
    A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges
    arXiv cs.CV/2110.14051, 2021
    [BibTeX] [PDF]

    @article{salehi2021unified,
      title={A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges},
      author={Mohammadreza Salehi and Hossein Mirzaei and Dan Hendrycks and Yixuan Li and Mohammad Hossein Rohban and Mohammad Sabokrou},
      journal={arXiv preprint arXiv:2110.14051},
      year={2021}
    }
    
  • Mu Cai, Hong Zhang, Huijuan Huang, Qichuan Geng, Yixuan Li and Gao Huang
    Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving
    In Proceedings of International Conference on Computer Vision (ICCV), 2021
    [BibTeX] [PDF] [Code]

    @article{cai2021frequency,
    title={Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving},
    author={Cai, Mu and Zhang, Hong and Huang, Huijuan and Geng, Qichuan and Li, Yixuan and Huang, Gao},
    journal={In Proceedings of International Conference on Computer Vision (ICCV)},
    year={2021}
    }
    
  • Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang and Somesh Jha
    ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
    In Proceedings of European Conference on Machine Learning (ECML-PKDD), 2021
    Acceptance Ratio: 21%
    [BibTeX] [PDF] [Code]

    @article{chen2021robustifying,
    title={ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining},
    author={Chen, Jiefeng and Li, Yixuan and Wu, Xi and Liang, Yingyu and Jha, Somesh},
    journal={In Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)},
    year={2021}
    }
    
  • Rui Huang and Yixuan Li
    MOS: Scaling Out-of-distribution Detection to Large Semantic Space
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
    Oral Presentation, Acceptance Ratio: ~4%
    [BibTeX] [PDF] [Code]

    @inproceedings{huang2021mos,
      title={MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space},
      author={Huang, Rui and Li, Yixuan},
      booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
      year={2021}
    }
    
  • Ziqian Lin*, Sreya Dutta Roy* and Yixuan Li
    MOOD: Multi-level Out-of-distribution Detection
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
    * indicates equal contribution
    [BibTeX] [PDF] [Code]

      @inproceedings{lin2021mood,
      author    = {Lin, Ziqian  and Roy, Sreya Dutta  and Li, Yixuan},
      title     = {MOOD: Multi-level Out-of-distribution Detection},
      booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
      year      = {2021}
    }
    
  • Yiyou Sun*, Bastin Joseph*, Alison Deatsch, Robert Jeraj and Yixuan Li
    LOOD: Localization-based Uncertainty Estimation for Medical Imaging
    International Conference on Machine Learning (ICML DFUQ Workshop), 2021.
    Spotlight paper
    [BibTeX]

    
    
  • Karan Goel*, Albert Gu*, Yixuan Li and Christopher Ré
    Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
    In Proceedings of the 9th International Conference on Learning Representations (ICLR), 2021
    * indicates equal contribution
    [BibTeX] [PDF] [Blog] [Video] [Code]

    @article{goel2020model,
    title={Model Patching: Closing the Subgroup Performance Gap with Data Augmentation},
    author={Goel, Karan and Gu, Albert and Li, Yixuan and Ré, Christopher},
    journal={Proceedings of the International Conference on Learning Representations (ICLR)},
    year={2021}
    }
    
  • Weitang Liu, Xiaoyun Wang, John Owens and Yixuan Li
    Energy-based Out-of-distribution Detection
    Neural Information Processing Systems (NeurIPS), 2020
    [BibTeX] [PDF] [Code]

    @article{liu2020energy,
    title={Energy-based Out-of-distribution Detection},
    author={Liu, Weitang and Wang, Xiaoyun and Owens, John and Li, Yixuan},
    journal={Advances in Neural Information Processing Systems (NeurIPS)},
    year={2020}
    }
    
  • Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang and Somesh Jha
    Informative Outlier Matters: Robustifying Out-of-distribution Detection Using Outlier Mining
    ICML workshop on Uncertainty and Robustness in Deep Learning (ICML UDL), 2020
    [BibTeX] [PDF]

    
    
  • Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang and Somesh Jha
    Robust Out-of-distribution Detection for Neural Networks
    arXiv cs.LG/2003.09711, 2020
    [BibTeX] [PDF]

    @article{chen2020robust,
    title={Robust Out-of-distribution Detection in Neural Networks},
    author={Chen, Jiefeng and Li, Yixuan and Wu, Xi and Liang, Yingyu and Jha, Somesh},
    journal={arXiv},
    pages={arXiv--2003},
    year={2020}
    }
    
  • Trenton Chang, Dan Fu, Yixuan Li, and Chris Ré
    Beyond the Pixels: Exploring the Effect of Video File Corruptions on Model Robustness
    ECCV Workshop, 2020
    [PDF] [Slides] [Video]

  • Yina Tang*, Fedor Borisyuk*, Siddarth Malreddy*, Yixuan Li*, Yiqun Liu* and Sergey Kirshner*
    MSURU: Large Scale E-commerce Image Classification With Weakly Supervised Search Data
    In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), 2019
    * indicates equal contribution
    [BibTeX] [PDF]

    @inproceedings{tang2019msuru,
      title={MSURU: Large Scale E-commerce Image Classification with Weakly Supervised Search Data},
      author={Tang, Yina and Borisyuk, Fedor and Malreddy, Siddarth and Li, Yixuan and Liu, Yiqun and Kirshner, Sergey},
      booktitle={Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
      pages={2518--2526},
      year={2019}
    }
    
  • Abhinmanyu Dubey, Laurens van der Maaten, Zeki Yalniz, Yixuan Li and Dhruv Mahajan
    Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
    Oral Presentation
    [BibTeX] [PDF]

    @article{dubey2019defense,
    title={Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search},
    author={Dubey, Abhimanyu and van der Maaten, Laurens and Yalniz, Zeki and Li, Yixuan and Mahajan, Dhruv},
    journal={arXiv preprint arXiv:1903.01612},
    year={2019}
    }
    
  • Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens van der Maaten
    Exploring the Limits of Weakly Supervised Pretraining
    In Proceedings of European Conference on Computer Vision (ECCV), 2018.
    [BibTeX] [PDF] [Blob Post]

    @inproceedings{mahajan2018exploring,
      title={Exploring the limits of weakly supervised pretraining},
      author={Mahajan, Dhruv and Girshick, Ross and Ramanathan, Vignesh and He, Kaiming and Paluri, Manohar and Li, Yixuan and Bharambe, Ashwin and Van Der Maaten, Laurens},
      booktitle={Proceedings of the European conference on computer vision (ECCV)},
      pages={181--196},
      year={2018}
    }
    
  • Shiyu Liang, Ruoyu Sun, Yixuan Li, R. Srikant,
    Understanding the Loss Surface of Neural Networks for Binary Classification
    In Proceedings of International Conference on Machine Learning (ICML), 2018.
    Oral Presentation
    [BibTeX] [PDF]

    @inproceedings{liang2018understanding,
      author = {Shiyu Liang, Ruoyu Sun, Yixuan Li, R. Srikant},
      title = {Understanding the Loss Surface of Neural Networks for Binary Classification},
      booktitle = {International Conference on Machine Learning (ICML)},
      year = {2018}
    }
    
  • Shiyu Liang, Ruoyu Sun, Yixuan Li, R. Srikant
    Understanding the Loss Surface of Single-Layered Neural Networks for Binary Classification
    International Conference on Learning Representation (ICLR Workshop), 2018
    [BibTeX] [PDF]

      @article{liang2018understanding,
        title={Understanding the Loss Surface of Single-Layered Neural Networks for Binary Classification},
        author={Liang, Shiyu and Sun, Ruoyu and Li, Yixuan and Srikant, R},
        year={2018}
      }
    
  • Shiyu Liang, Yixuan Li, R. Srikant
    Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
    In Proceedings of the 6th International Conference on Learning Representations (ICLR), 2018.
    [BibTeX] [PDF]

    @article{liang2017enhancing,
      title={Enhancing the reliability of out-of-distribution image detection in neural networks},
      author={Liang, Shiyu and Li, Yixuan and Srikant, R},
      journal={International Conference on Learning Representations (ICLR)},
      year={2018}
    }
    
  • Gao Huang*, Yixuan Li*, Geoff Pleiss, Zhuang Liu, John Hopcroft and Kilian Weinberger
    Snapshot Ensembles: Train 1, Get M for Free
    In Proceedings of the 5th International Conference on Learning Representations (ICLR), 2017.
    * indicates equal contribution
    [BibTeX] [PDF] [Code]

    @article{huang2017snapshot,
      title={Snapshot ensembles: Train 1, get M for free},
      author={Huang, Gao and Li, Yixuan and Pleiss, Geoff and Liu, Zhuang and Hopcroft, John E and Weinberger, Kilian Q},
      journal={International Conference on Learning Representations (ICLR)},
      year={2017}
    }
    
  • Xun Huang, Yixuan Li,Omid Poursaeed, John Hopcroft, and Serge Belongie
    Stacked Adversarial Generative Networks
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
    [BibTeX] [PDF] [Code]

    @inproceedings{huang2017stacked,
      title={Stacked Generative Adversarial Networks.},
      author={Huang, Xun and Li, Yixuan and Poursaeed, Omid and Hopcroft, John E and Belongie, Serge J},
      booktitle={CVPR},
      volume={2},
      pages={3},
      year={2017}
    }
    
  • Yixuan Li, Pingmei Xu, Dmitry Lagun and Vidhya Navalpakkam
    Towards Measuring and Inferring User Interest From Gaze
    In Proceedings of the 26th international conference on World Wide Web (WWW), 2017
    Oral Presentation
    [BibTeX] [PDF]

    @inproceedings{li2017towards,
      title={Towards measuring and inferring user interest from gaze},
      author={Li, Yixuan and Xu, Pingmei and Lagun, Dmitry and Navalpakkam, Vidhya},
      booktitle={Proceedings of the 26th International Conference on World Wide Web Companion},
      pages={525--533},
      year={2017},
      organization={International World Wide Web Conferences Steering Committee}
    }
    
  • Yixuan Li, Kun He, Kyle Kloster, David Bindel, and John Hopcroft
    Local spectral clustering for overlapping community detection
    In ACM Transactions on Knowledge Discovery from Data (TKDD), 2017.
    [BibTeX] [PDF]

    @article{li2018local,
      title = {Local spectral clustering for overlapping community detection},
      author = {Li, Yixuan and He, Kun and Kloster, Kyle and Bindel, David and Hopcroft, John},
      journal = {ACM Transactions on Knowledge Discovery from Data (TKDD)},
      volume = {12},
      number = {2},
      pages = {17},
      year = {2018},
      publisher = {ACM}
    }
    
  • Yixuan Li, Jason Yosinski, Jeff Clune, John Hopcroft, and Hod Lipson
    Convergent Learning: Do different neural networks learn the same representations?
    In Proceedings of the 4th International Conference on Learning Representation (ICLR), 2016
    Oral Presentation, Acceptance Ratio: 5.7%
    [BibTeX] [PDF] [Code]

    @inproceedings{li2015convergent,
      title={Convergent learning: Do different neural networks learn the same representations?},
      author={Li, Yixuan and Yosinski, Jason and Clune, Jeff and Lipson, Hod and Hopcroft, John E},
      booktitle = {International Conference on Learning Representations (ICLR)},
      year={2016}
    }
    
  • Yixuan Li, Oscar Martinez, Xing Chen, Yi Li and John Hopcroft
    In a World that Counts: Clustering and Detecting Fake Social Engagement at Scale
    In Proceedings of the 25th international conference on World Wide Web (WWW), 2016
    Oral Presentation
    [BibTeX] [PDF] [Press]

    @inproceedings{li2016world,
      title={In a world that counts: Clustering and detecting fake social engagement at scale},
      author={Li, Yixuan and Martinez, Oscar and Chen, Xing and Li, Yi and Hopcroft, John E},
      booktitle={Proceedings of the 25th International Conference on World Wide Web},
      pages={111--120},
      year={2016},
      organization={International World Wide Web Conferences Steering Committee}
    }
    
  • Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang and John Hopcroft
    The Lifecycle and Cascade of Social Messaging Groups
    In Proceedings of the 25th international conference on World Wide Web (WWW), 2016
    Oral Presentation
    [BibTeX] [PDF]

    @inproceedings{qiu2016lifecycle,
    title={The lifecycle and cascade of wechat social messaging groups},
    author={Qiu, Jiezhong and Li, Yixuan and Tang, Jie and Lu, Zheng and Ye, Hao and Chen, Bo and Yang, Qiang and Hopcroft, John E},
    booktitle={Proceedings of the 25th International Conference on World Wide Web},
    pages={311--320},
    year={2016},
    organization={International World Wide Web Conferences Steering Committee}
    }
    
  • Kyle Kloster, Yixuan Li
    Scalable and Robust Local Community Detection via Adaptive Subgraph Extraction and Diffusions
    Preprint on arXiv., 2016
    [BibTeX] [PDF]

    @article{kloster2016scalable,
      title={Scalable and Robust Local Community Detection via Adaptive Subgraph Extraction and Diffusions},
      author={Kloster, Kyle and Li, Yixuan},
      journal={arXiv preprint arXiv:1611.05152},
      year={2016}
    }
    
  • Jacob Gardner, Paul Upchurch, Matt Kusner,Yixuan Li, Kilian Weinberger, Kavita Bala and John Hopcroft
    Deep Manifold Traversal: Changing Labels with Convolutional Features
    arXiv cs.LG/1511.06421, 2015
    [BibTeX] [PDF]

    @article{gardner2015deep,
      title={Deep manifold traversal: Changing labels with convolutional features},
      author={Gardner, Jacob R and Upchurch, Paul and Kusner, Matt J and Li, Yixuan and Weinberger, Kilian Q and Bala, Kavita and Hopcroft, John E},
      journal={arXiv preprint arXiv:1511.06421},
      year={2015}
    }
    
  • Yixuan Li, Jason Yosinski, Jeff Clune, John Hopcroft and Hod Lipson
    Convergent Learning: Do different neural networks learn the same representations?
    NIPS Workshop on Feature Extraction: Modern Questions and Challenges (NIPS Workshop), 2015.
    (Selected oral presentation: 6.7%)
    [BibTeX] [PDF]

      @inproceedings{li2015convergent_b,
        title={Convergent learning: Do different neural networks learn the same representations?},
        author={Li, Yixuan and Yosinski, Jason and Clune, Jeff and Lipson, Hod and Hopcroft, John E},
        booktitle={FE@ NIPS},
        pages={196--212},
        year={2015}
      }
    
  • Yixuan Li, Kun He, David Bindel and John Hopcroft
    Uncovering the Small Community Structure in Large Networks: A Local Spectral Approach
    In Proceedings of the 24th International Conference on World Wide Web (WWW), 2015
    Oral presentation, Acceptance ratio: 14.1%
    [BibTeX] [PDF]

    @inproceedings{li2015uncovering,
      title={Uncovering the small community structure in large networks: A local spectral approach},
      author={Li, Yixuan and He, Kun and Bindel, David and Hopcroft, John E},
      booktitle={Proceedings of the 24th international conference on world wide web},
      pages={658--668},
      year={2015},
      organization={International World Wide Web Conferences Steering Committee}
    }
    
  • Kun He, Yiwei Sun, David Bindel and John Hopcroft, Yixuan Li
    Detecting Overlapping Communities from Local Spectral Subspaces
    In Proceedings of the International Conference on Data Mining (ICDM), 2015
    [BibTeX] [PDF]

    @inproceedings{he2015detecting,
      title={Detecting overlapping communities from local spectral subspaces},
      author={He, Kun and Sun, Yiwei and Bindel, David and Hopcroft, John and Li, Yixuan},
      booktitle={Data Mining (ICDM), 2015 IEEE International Conference on},
      pages={769--774},
      year={2015},
      organization={IEEE}
    }
    
  • J. Zhang, Yixuan Li, Z. Liu, F. Wu,F. Yang, and X. Wang
    On Multicast Capacity and Delay in Cognitive Radio Mobile Ad-hoc Networks IEEE Transactions on Wireless Communications (TWC), 2015.
    [BibTeX] [PDF]

    @article{zhang2015multicast,
    title={On multicast capacity and delay in cognitive radio mobile ad hoc networks},
    author={Zhang, Jinbei and Li, Yixuan and Liu, Zhuotao and Wu, Fan and Yang, Feng and Wang, Xinbing},
    journal={IEEE Transactions on Wireless Communications},
    volume={14},
    number={10},
    pages={5274--5286},
    year={2015},
    publisher={IEEE}
    }
    
  • Yixuan Li,Qiuyu Peng, and Xinbing Wang
    Multicast Capacity With Max-Min Fairness for Heterogeneous Networks
    In IEEE/ACM Transactions on Networking (TON), 2014
    [BibTeX] [PDF]

    @article{li2014multicast,
    title={Multicast capacity with max-min fairness for heterogeneous networks},
    author={Li, Yixuan and Peng, Qiuyu and Wang, Xinbing},
    journal={IEEE/ACM Transactions on Networking (TON)},
    volume={22},
    number={2},
    pages={622--635},
    year={2014},
    publisher={IEEE Press}
    }