February, 2024
<p>One paper titled Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization has been accepted at Conference on Computer Vision and Pattern Recognition 2024 (CVPR’24).
</em></p>
January, 2024
<p>One paper titled Towards Efficient Communication Federated Recommendation System via Low-rank Training has been accepted at The Web Conference 2024 (WWW’24). You can access the paper here.
</em></p>
January, 2024
<p>One paper titled Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks has been accepted at International Conference on Learning Representations (ICLR’24). You can access the paper here.
</em></p>
January, 2024
<p>One paper titled Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning has been accepted by IEEE Transactions on Emerging Topics in Computing. You can access the paper here.
</em></p>
January, 2024
<p>Congrats, Le Huy Khiem will pursue his Ph.D. at the University of Notre Dame, USA under the supervision of Prof. Nitesh Vijay Chawla.
</em></p>
December, 2023
<p>We attended NeurIPS 2023. Our paper titled IBA: Towards Irreversible Backdoor Attacks in Federated Learning was presented at the conference. The paper is available here. We also oganized a workshop on Backdoors in Deep Learning - The Good, the Bad, and the Ugly. The recorded video is available here.
</em></p>
November, 2023
<p>One paper titled FedFSLAR: A Federated Learning Framework for Few-shot Action Recognition has been accepted at IEEE/CVF Winter Conference on Applications of Computer Vision (WACV2024) Workshop.
</em></p>
November, 2023
<p>SAIL and MAIL lab members participated in ACML conference 2023. Tuan Nguyen presented our paper titled An Empirical Study of Federated Unlearning: Efficiency and Effectiveness. The code is available here.
</em></p>
September 2023
<p>Our paper titled IBA: Towards Irreversible Backdoor Attacks in Federated Learning has been accepted at Conference on Neural Information Processing Systems (NeurIPS 2023). You can access the paper here.
</em></p>
September 2023
<p>Our survey paper titled Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions has been accepted at Engineering Applications of Artificial Intelligence (EAAI). You can access the paper here.
</em></p>
September 2023
<p>Our paper titled An Empirical Study of Federated Unlearning: Efficiency and Effectiveness has been accepted at Asian Conference on Machine Learning (ACML 2023). You can access the paper here.
</em></p>
August 2023
<p>Congrats, Nguyen Thuy Dung will pursue her Ph.D. at the University of Valderbilt, USA
</em></p>
July 2023
<p>Congrats, Our BUG workshop proposal on Backdoors in Deep Learning - The Good, the Bad, and the Ugly got accepted at NeurIPS 2023.
</em></p>
May 2023
<p>New paper on arXiv! An Empirical Study of Federated Learning on IoT-Edge Devices: Resource Allocation and Heterogeneity.
</em></p>
May 2023
<p>Our paper titled FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection has been accepted at The International Joint Conference on Neural Networks (IJCNN 2023). You can access the paper here.
</em></p>
March 2023
<p>One paper titled Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions. You can access the paper here.
</em></p>
January 2023
<p>Congrats, Tuan Nguyen is now a Ph.D. Candidate!
</em></p>