4 citations · 5 across the 4 of their papers we have counts for
4 papers
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
Cheng-Hao Tu, Hong-You Chen, Zheda Mai +7
We propose a learning problem involving adapting a pre-trained source model to the target domain for classifying all classes that appeared in the source data, using target data tha…
Federated Learning of Shareable Bases for Personalization-Friendly Image Classification
Hong-You Chen, Jike Zhong, Mingda Zhang +5
Personalized federated learning (PFL) aims to harness the collective wisdom of clients' data while building personalized models tailored to individual clients' data distributions.…
Making Batch Normalization Great in Federated Deep Learning
Jike Zhong, Hong-You Chen, Wei-Lun Chao
Batch Normalization (BN) is widely used in {centralized} deep learning to improve convergence and generalization. However, in {federated} learning (FL) with decentralized data, pri…
Learning with Free Object Segments for Long-Tailed Instance Segmentation
Cheng Zhang, Tai-Yu Pan, Tianle Chen +3
One fundamental challenge in building an instance segmentation model for a large number of classes in complex scenes is the lack of training examples, especially for rare objects.…