49 citations · 103 across the 21 of their papers we have counts for
4 papers · 1 filter
How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning
Shuo Wan, Jiaxun Lu, Pingyi Fan +3
Federated learning (FL) has recently emerged as a transformative paradigm that jointly train a model with distributed data sets in IoT while avoiding the need for central data coll…
Unified Group Fairness on Federated Learning
Fengda Zhang, Kun Kuang, Yuxuan Liu +6
Federated learning (FL) has emerged as an important machine learning paradigm where a global model is trained based on the private data from distributed clients. However, most of e…
Convergence Analysis and System Design for Federated Learning over Wireless Networks
Shuo Wan, Jiaxun Lu, Pingyi Fan +3
Federated learning (FL) has recently emerged as an important and promising learning scheme in IoT, enabling devices to jointly learn a model without sharing their raw data sets. Ho…
Active and Adaptive Sequential learning
Yuheng Bu, Jiaxun Lu, Venugopal V. Veeravalli
A framework is introduced for actively and adaptively solving a sequence of machine learning problems, which are changing in bounded manner from one time step to the next. An algor…