1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
CAAP: Class-Dependent Automatic Data Augmentation Based On Adaptive Policies For Time Series
Tien-Yu Chang, Hao Dai, Vincent S. Tseng
Data Augmentation is a common technique used to enhance the performance of deep learning models by expanding the training dataset. Automatic Data Augmentation (ADA) methods are get…
cs.CV2023
Multi-view knowledge distillation transformer for human action recognition
Ying-Chen Lin, Vincent S. Tseng
Recently, Transformer-based methods have been utilized to improve the performance of human action recognition. However, most of these studies assume that multi-view data is complet…
cs.LG2023★ 1 cited
FLAG: Fast Label-Adaptive Aggregation for Multi-label Classification in Federated Learning
Shih-Fang Chang, Benny Wei-Yun Hsu, Tien-Yu Chang +1
Federated learning aims to share private data to maximize the data utility without privacy leakage. Previous federated learning research mainly focuses on multi-class classificatio…