no code implementations • 8 Apr 2024 • Khoi Do, Duong Nguyen, Nguyen H. Tran, Viet Dung Nguyen
First, the class-wise gradient magnitude homogenization helps alleviate the imbalance among label masks by ensuring equal consideration of the class-wise impact on model updates.
no code implementations • 27 Sep 2023 • Long Tan Le, Tuan Dung Nguyen, Tung-Anh Nguyen, Choong Seon Hong, Nguyen H. Tran
Federated Learning (FL) is a prominent distributed learning paradigm facilitating collaboration among nodes within an edge network to co-train a global model without centralizing data.
no code implementations • 23 Dec 2022 • Tung-Anh Nguyen, Jiayu He, Long Tan Le, Wei Bao, Nguyen H. Tran
To the best of our knowledge, this is the first federated PCA algorithm for anomaly detection meeting the requirements of IoT networks.
1 code implementation • British Machine Vision Conference (BMVC) 2022 • Nguyen H. Tran, Ta Duc Huy, Soan T. M. Duong, Phan Nguyen, Dao Huu Hung, Chanh D. Tr. Nguyen, Trung Bui, Steven Q.H. Truong
ViT is adapted on each patch to employ the attention mechanism across the 3 × 3 cells to count the number of people in the central cell.
Ranked #4 on Crowd Counting on ShanghaiTech A
no code implementations • 3 Jun 2022 • Tung-Anh Nguyen, Tuan Dung Nguyen, Long Tan Le, Canh T. Dinh, Nguyen H. Tran
We show that the robustness of WAFL is more general than related approaches, and the generalization bound is robust to all adversarial distributions inside the Wasserstein ball (ambiguity set).
2 code implementations • 14 Feb 2021 • Canh T. Dinh, Tung T. Vu, Nguyen H. Tran, Minh N. Dao, Hongyu Zhang
Non-Independent and Identically Distributed (non- IID) data distribution among clients is considered as the key factor that degrades the performance of federated learning (FL).
2 code implementations • 10 Dec 2020 • Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen, Wei Bao, Amir Rezaei Balef, Bing B. Zhou, Albert Y. Zomaya
In this work, we propose DONE, a distributed approximate Newton-type algorithm with fast convergence rate for communication-efficient federated edge learning.
no code implementations • 1 Dec 2020 • Shashi Raj Pandey, Minh N. H. Nguyen, Tri Nguyen Dang, Nguyen H. Tran, Kyi Thar, Zhu Han, Choong Seon Hong
Therefore, we need to design a robust learning mechanism than the FL that (i) unleashes a viable infrastructure for FA and (ii) trains learning models with better generalization capability.
1 code implementation • 25 Nov 2020 • Minh N. H. Nguyen, Nguyen H. Tran, Yan Kyaw Tun, Zhu Han, Choong Seon Hong
Federated Learning is a new learning scheme for collaborative training a shared prediction model while keeping data locally on participating devices.
no code implementations • 22 Sep 2020 • Tra Huong Thi Le, Nguyen H. Tran, Yan Kyaw Tun, Minh N. H. Nguyen, Shashi Raj Pandey, Zhu Han, Choong Seon Hong
In this paper, we consider a FL system that involves one base station (BS) and multiple mobile users.
no code implementations • 18 Sep 2020 • Zhengjie Yang, Wei Bao, Dong Yuan, Nguyen H. Tran, Albert Y. Zomaya
It is well-known that Nesterov Accelerated Gradient (NAG) is a more advantageous form of momentum, but it is not clear how to quantify the benefits of NAG in FL so far.
1 code implementation • 4 Sep 2020 • Tung T. Vu, Duy T. Ngo, Hien Quoc Ngo, Minh N. Dao, Nguyen H. Tran, Richard H. Middleton
We then develop a new algorithm that is proven to converge to the neighbourhood of the stationary points of the formulated problem.
Information Theory Information Theory
1 code implementation • 7 Jul 2020 • Minh N. H. Nguyen, Shashi Raj Pandey, Tri Nguyen Dang, Eui-Nam Huh, Nguyen H. Tran, Walid Saad, Choong Seon Hong
Inspired by Dem-AI philosophy, a novel distributed learning approach is proposed in this paper.
4 code implementations • NeurIPS 2020 • Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen
Federated learning (FL) is a decentralized and privacy-preserving machine learning technique in which a group of clients collaborate with a server to learn a global model without sharing clients' data.
no code implementations • 28 Apr 2020 • Dai Hoang Tran, Quan Z. Sheng, Wei Emma Zhang, Salma Abdalla Hamad, Munazza Zaib, Nguyen H. Tran, Lina Yao, Nguyen Lu Dang Khoa
In recent years, the emerging topics of recommender systems that take advantage of natural language processing techniques have attracted much attention, and one of their applications is the Conversational Recommender System (CRS).
1 code implementation • 18 Mar 2020 • Minh N. H. Nguyen, Shashi Raj Pandey, Kyi Thar, Nguyen H. Tran, Mingzhe Chen, Walid Saad, Choong Seon Hong
Consequently, many emerging cross-device AI applications will require a transition from traditional centralized learning systems towards large-scale distributed AI systems that can collaboratively perform multiple complex learning tasks.
no code implementations • 21 Feb 2020 • Md. Shirajum Munir, Sarder Fakhrul Abedin, Nguyen H. Tran, Zhu Han, Eui-Nam Huh, Choong Seon Hong
First, we formulate an optimization problem considering the conditional value-at-risk (CVaR) measurement for both energy consumption and generation, where the objective is to minimize the expected residual of scheduled energy for the MEC networks and we show this problem is an NP-hard problem.
no code implementations • 21 Feb 2020 • Sarder Fakhrul Abedin, Md. Shirajum Munir, Nguyen H. Tran, Zhu Han, Choong Seon Hong
First, we formulate an energy-efficient trajectory optimization problem in which the objective is to maximize the energy efficiency by optimizing the UAV-BS trajectory policy.
no code implementations • 20 Feb 2020 • Md. Shirajum Munir, Nguyen H. Tran, Walid Saad, Choong Seon Hong
In particular, each BS plays the role of a local agent that explores a Markovian behavior for both energy consumption and generation while each BS transfers time-varying features to a meta-agent.
no code implementations • 6 Nov 2019 • Latif U. Khan, Nguyen H. Tran, Shashi Raj Pandey, Walid Saad, Zhu Han, Minh N. H. Nguyen, Choong Seon Hong
IoT devices with intelligence require the use of effective machine learning paradigms.
Distributed, Parallel, and Cluster Computing
no code implementations • 4 Nov 2019 • Shashi Raj Pandey, Nguyen H. Tran, Mehdi Bennis, Yan Kyaw Tun, Aunas Manzoor, Choong Seon Hong
Federated learning (FL) rests on the notion of training a global model in a decentralized manner.
4 code implementations • 29 Oct 2019 • Canh T. Dinh, Nguyen H. Tran, Minh N. H. Nguyen, Choong Seon Hong, Wei Bao, Albert Y. Zomaya, Vincent Gramoli
There is an increasing interest in a fast-growing machine learning technique called Federated Learning, in which the model training is distributed over mobile user equipments (UEs), exploiting UEs' local computation and training data.
no code implementations • 27 Sep 2019 • Tung T. Vu, Duy T. Ngo, Nguyen H. Tran, Hien Quoc Ngo, Minh N. Dao, Richard H. Middleton
This paper proposes a novel scheme for cell-free massive multiple-input multiple-output (CFmMIMO) networks to support any federated learning (FL) framework.
Signal Processing Information Theory Information Theory
no code implementations • 25 Dec 2018 • Dai Hoang Tran, Zawar Hussain, Wei Emma Zhang, Nguyen Lu Dang Khoa, Nguyen H. Tran, Quan Z. Sheng
Specifically, we find that DAE parameters strongly affect the prediction accuracy of the recommender systems, and the effect is transferable to similar datasets in a larger size.