5 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
FedBug: A Bottom-Up Gradual Unfreezing Framework for Federated Learning
Chia-Hsiang Kao, Yu-Chiang Frank Wang
Federated Learning (FL) offers a collaborative training framework, allowing multiple clients to contribute to a shared model without compromising data privacy. Due to the heterogen…
cs.LG2021★ 5 cited
MAML is a Noisy Contrastive Learner in Classification
Chia-Hsiang Kao, Wei-Chen Chiu, Pin-Yu Chen
Model-agnostic meta-learning (MAML) is one of the most popular and widely adopted meta-learning algorithms, achieving remarkable success in various learning problems. Yet, with the…