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2020 – today
- 2024
[j4]Canh T. Dinh
, Tung Thanh Vu, Nguyen Hoang Tran, Minh N. Dao, Hongyu Zhang:
A New Look and Convergence Rate of Federated Multitask Learning With Laplacian Regularization. IEEE Trans. Neural Networks Learn. Syst. 35(6): 8075-8085 (2024)- 2023
- [c4]Phuong Luu Vo, Nghia T. Nguyen, Long Luu, Canh T. Dinh, Nguyen Hoang Tran, Tuan-Anh Le:
Federated Deep Reinforcement Learning - Based Bitrate Adaptation for Dynamic Adaptive Streaming over HTTP. ACIIDS (Companion) 2023: 279-290 - [i7]Phuong Luu Vo, Nghia T. Nguyen, Long Luu, Canh T. Dinh, Nguyen Hoang Tran, Tuan-Anh Le:
Federated Deep Reinforcement Learning-based Bitrate Adaptation for Dynamic Adaptive Streaming over HTTP. CoRR abs/2306.15860 (2023) - 2022
- [j3]Canh T. Dinh, Nguyen Hoang Tran, Tuan Dung Nguyen, Wei Bao, Amir Rezaei Balef, Bing Bing Zhou, Albert Y. Zomaya:
DONE: Distributed Approximate Newton-type Method for Federated Edge Learning. IEEE Trans. Parallel Distributed Syst. 33(11): 2648-2660 (2022) - [c3]Tung Thanh Vu, Trinh Van Chien, Canh T. Dinh, Hien Quoc Ngo, Michail Matthaiou:
Channel Estimation in RIS-assisted Downlink Massive MIMO: A Learning-Based Approach. SPAWC 2022: 1-5 - [i6]Tung Thanh Vu, Trinh Van Chien, Canh T. Dinh, Hien Quoc Ngo, Michail Matthaiou:
Channel Estimation in RIS-assisted Downlink Massive MIMO: A Learning-Based Approach. CoRR abs/2205.05577 (2022) - [i5]Tung-Anh Nguyen, Tuan Dung Nguyen, Long Tan Le, Canh T. Dinh, Nguyen Hoang Tran:
On the Generalization of Wasserstein Robust Federated Learning. CoRR abs/2206.01432 (2022) - 2021
- [j2]Tuan Dung Nguyen, Amir Rezaei Balef, Canh T. Dinh, Nguyen Hoang Tran, Duy T. Ngo, Tuan Anh Le, Phuong Luu Vo:
Accelerating Federated Edge Learning. IEEE Commun. Lett. 25(10): 3282-3286 (2021) - [j1]Canh T. Dinh, Nguyen Hoang Tran, Minh N. H. Nguyen, Choong Seon Hong, Wei Bao, Albert Y. Zomaya, Vincent Gramoli:
Federated Learning Over Wireless Networks: Convergence Analysis and Resource Allocation. IEEE/ACM Trans. Netw. 29(1): 398-409 (2021) - [i4]Canh T. Dinh, Tung Thanh Vu, Nguyen Hoang Tran, Minh N. Dao, Hongyu Zhang:
FedU: A Unified Framework for Federated Multi-Task Learning with Laplacian Regularization. CoRR abs/2102.07148 (2021) - 2020
- [c2]Canh T. Dinh, Nguyen Hoang Tran, Tuan Dung Nguyen, Wei Bao, Albert Y. Zomaya, Bing Bing Zhou:
Federated Learning with Proximal Stochastic Variance Reduced Gradient Algorithms. ICPP 2020: 48:1-48:11 - [c1]Canh T. Dinh, Nguyen Hoang Tran, Tuan Dung Nguyen:
Personalized Federated Learning with Moreau Envelopes. NeurIPS 2020 - [i3]Canh T. Dinh, Nguyen Hoang Tran, Tuan Dung Nguyen:
Personalized Federated Learning with Moreau Envelopes. CoRR abs/2006.08848 (2020) - [i2]Canh T. Dinh, Nguyen Hoang Tran, Tuan Dung Nguyen, Wei Bao, Amir Rezaei Balef:
DONE: Distributed Newton-type Method for Federated Edge Learning. CoRR abs/2012.05625 (2020)
2010 – 2019
- 2019
- [i1]Canh T. Dinh, Nguyen Hoang Tran, Minh N. H. Nguyen, Choong Seon Hong, Wei Bao, Albert Y. Zomaya, Vincent Gramoli:
Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation. CoRR abs/1910.13067 (2019)
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