Yaxin Li

Orcid: 0000-0002-6227-7844

Affiliations:
  • Michigan State University, East Lansing, MI, USA


According to our database1, Yaxin Li authored at least 20 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Neural Style Protection: Counteracting Unauthorized Neural Style Transfer.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention.
Proceedings of the Computer Vision - ECCV 2024, 2024

Exploring Memorization in Fine-tuned Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Trustworthy AI: A Computational Perspective.
ACM Trans. Intell. Syst. Technol., February, 2023

A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Enhancing Adversarial Training with Feature Separability.
CoRR, 2022

Towards Practical Robustness Evaluation and Robustness Enhancing.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Imbalanced Adversarial Training with Reweighting.
Proceedings of the IEEE International Conference on Data Mining, 2022

2021
Trustworthy AI: A Computational Perspective.
CoRR, 2021

Yet Meta Learning Can Adapt Fast, it Can Also Break Easily.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Adversarial Robustness in Deep Learning: From Practices to Theories.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

To be Robust or to be Fair: Towards Fairness in Adversarial Training.
Proceedings of the 38th International Conference on Machine Learning, 2021

Elastic Graph Neural Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

DeepRobust: a Platform for Adversarial Attacks and Defenses.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Adversarial Attacks and Defenses on Graphs.
SIGKDD Explor., 2020

To be Robust or to be Fair: Towards Fairness in Adversarial Training.
CoRR, 2020

DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses.
CoRR, 2020

Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study.
CoRR, 2020

Adversarial Attacks and Defenses: Frontiers, Advances and Practice.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Graphical Evolutionary Game Theoretic Analysis of Super Users in Information Diffusion.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020


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