12 citations · 21 across the 6 of their papers we have counts for
6 papers
Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder
Duy A. Nguyen, Trang H. Tran, Huy Hieu Pham +2
In this work, we investigate the time series representation learning problem using self-supervised techniques. Contrastive learning is well-known in this area as it is a powerful m…
Multimodal contrastive learning for diagnosing cardiovascular diseases from electrocardiography (ECG) signals and patient metadata
Tue M. Cao, Nhat H. Tran, Phi Le Nguyen +1
This work discusses the use of contrastive learning and deep learning for diagnosing cardiovascular diseases from electrocardiography (ECG) signals. While the ECG signals usually c…
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions
Thuy Dung Nguyen, Tuan Nguyen, Phi Le Nguyen +3
Federated learning (FL) is a machine learning (ML) approach that allows the use of distributed data without compromising personal privacy. However, the heterogeneous distribution o…
Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Prediction
Thanh Trung Huynh, Minh Hieu Nguyen, Thanh Tam Nguyen +4
Advances in deep neural network (DNN) architectures have enabled new prediction techniques for stock market data. Unlike other multivariate time-series data, stock markets show two…
FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Collaborative Training
Quan Nguyen, Hieu H. Pham, Kok-Seng Wong +3
We introduce FedDCT, a novel distributed learning paradigm that enables the usage of large, high-performance CNNs on resource-limited edge devices. As opposed to traditional FL app…
Multi-stream Fusion for Class Incremental Learning in Pill Image Classification
Trong-Tung Nguyen, Hieu H. Pham, Phi Le Nguyen +2
Classifying pill categories from real-world images is crucial for various smart healthcare applications. Although existing approaches in image classification might achieve a good p…