Publications

Preprints

Tung-Anh Nguyen, Tuan Dung Nguyen, Long Tan Le, Canh T. Dinh, and Nguyen H. Tran. “On the Generalization of Wasserstein Robust Federated Learning.” arXiv:2206.01432 (2022). [Paper] [Code]

2022

Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen, Wei Bao, Amir Rezaei Balef, Bing B. Zhou, and Albert Y. Zomaya. “DONE: Distributed Approximate Newton-type Method for Federated Edge Learning”. In: IEEE Transactions on Parallel and Distributed Systems 33.11 (2022), pp. 2648–2660. [Paper] [Code]

Tuan Dung Nguyen, Georgiana Lyall, Alasdair Tran, Minjeong Shin, Nicholas George Carroll, Colin Klein, and Lexing Xie. “Mapping Topics in 100,000 Real-Life Moral Dilemmas”. In: Proceedings of the International AAAI Conference on Web and Social Media 16.1 (2022), pp. 699–710. [Paper] [Code] [Data] [Poster] [Presentation] [Slides]

2021

Tuan Dung Nguyen, Amir R. Balef, Canh T. Dinh, Nguyen H. Tran, Duy T. Ngo, Tuan Anh Le, and Phuong L. Vo. “Accelerating Federated Edge Learning”. In: IEEE Communications Letters 25.10 (2021), pp. 3282–3286. [Paper] [Code for AA]

2020

Canh T. Dinh, Nguyen H. Tran, and Tuan Dung Nguyen. “Personalized Federated Learning with Moreau Envelopes”. In: Advances in Neural Information Processing Systems 33. 2020, pp. 21394–21405. [Paper] [Code] [Presentation]

Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen, Wei Bao, Albert Y. Zomaya, and Bing B. Zhou. “Federated Learning with Proximal Stochastic Variance Reduced Gradient Algorithms”. In: 49th International Conference on Parallel Processing. 2020, pp. 1–11. [Paper] [Code] [Presentation]