10 citations · 29 across the 43 of their papers we have counts for
7 papers · 1 filter
Robust Collaborative Inference with Vertically Split Data Over Dynamic Device Environments
Surojit Ganguli, Zeyu Zhou, Christopher G. Brinton +1
When each edge device of a network only perceives a local part of the environment, collaborative inference across multiple devices is often needed to predict global properties of t…
The Impact of Adversarial Node Placement in Decentralized Federated Learning Networks
Adam Piaseczny, Eric Ruzomberka, Rohit Parasnis +1
As Federated Learning (FL) grows in popularity, new decentralized frameworks are becoming widespread. These frameworks leverage the benefits of decentralized environments to enable…
StableFDG: Style and Attention Based Learning for Federated Domain Generalization
Jungwuk Park, Dong-Jun Han, Jinho Kim +3
Traditional federated learning (FL) algorithms operate under the assumption that the data distributions at training (source domains) and testing (target domain) are the same. The f…
Digital Ethics in Federated Learning
Liangqi Yuan, Ziran Wang, Christopher G. Brinton
The Internet of Things (IoT) consistently generates vast amounts of data, sparking increasing concern over the protection of data privacy and the limitation of data misuse. Federat…
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates
Guangchen Lan, Han Wang, James Anderson +2
Federated reinforcement learning (FedRL) enables agents to collaboratively train a global policy without sharing their individual data. However, high communication overhead remains…
Federated Learning over Hierarchical Wireless Networks: Training Latency Minimization via Submodel Partitioning
Wenzhi Fang, Dong-Jun Han, Christopher G. Brinton
Hierarchical federated learning (HFL) has demonstrated promising scalability advantages over the traditional "star-topology" architecture-based federated learning (FL). However, HF…
FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication
Liangqi Yuan, Dong-Jun Han, Vishnu Pandi Chellapandi +2
Multimodal federated learning (FL) aims to enrich model training in FL settings where devices are collecting measurements across multiple modalities (e.g., sensors measuring pressu…