42 citations · 78 across the 8 of their papers we have counts for
4 papers · 1 filter
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang +7
Federated Learning (FL) is a distributed learning paradigm that can learn a global or personalized model from decentralized datasets on edge devices. However, in the computer visio…
On the Fairness of Swarm Learning in Skin Lesion Classification
Di Fan, Yifan Wu, Xiaoxiao Li
in healthcare. However, the existing AI model may be biased in its decision marking. The bias induced by data itself, such as collecting data in subgroups only, can be mitigated by…
Over-the-Air Federated Multi-Task Learning
Haoming Ma, Xiaojun Yuan, Dian Fan +3
In this letter, we introduce over-the-air computation into the communication design of federated multi-task learning (FMTL), and propose an over-the-air federated multi-task learni…
Temporal-Structure-Assisted Gradient Aggregation for Over-the-Air Federated Edge Learning
Dian Fan, Xiaojun Yuan, Ying-Jun Angela Zhang
In this paper, we investigate over-the-air model aggregation in a federated edge learning (FEEL) system. We introduce a Markovian probability model to characterize the intrinsic te…