1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025★ 1 cited
Multimodal Online Federated Learning with Modality Missing in Internet of Things
Heqiang Wang, Xiang Liu, Xiaoxiong Zhong +3
The Internet of Things (IoT) ecosystem generates vast amounts of multimodal data from heterogeneous sources such as sensors, cameras, and microphones. As edge intelligence continue…
cs.AI2025
CARE: Compatibility-Aware Incentive Mechanisms for Federated Learning with Budgeted Requesters
Xiang Liu, Hau Chan, Minming Li +3
Federated learning (FL) is a promising approach that allows requesters (\eg, servers) to obtain local training models from workers (e.g., clients). Since workers are typically unwi…
cs.NI2012
MEGCOM: Min-Energy Group COMmunication in Multi-hop Wireless Networks
Kai Han, Liu Xiang, Jun Luo +1
Given the increasing demand from wireless applications, designing energy-efficient group communication protocols is of great importance to multi-hop wireless networks. A group comm…