124 citations · 456 across the 38 of their papers we have counts for
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cs.LG2022★ 3 cited
Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression
Feijie Wu, Shiqi He, Song Guo +4
Traditional one-bit compressed stochastic gradient descent can not be directly employed in multi-hop all-reduce, a widely adopted distributed training paradigm in network-intensive…
cs.LG2021★ 7 cited
Efficient Federated Meta-Learning over Multi-Access Wireless Networks
Sheng Yue, Ju Ren, Jiang Xin +3
Federated meta-learning (FML) has emerged as a promising paradigm to cope with the data limitation and heterogeneity challenges in today's edge learning arena. However, its perform…
cs.LG2020
Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning
Wen Wu, Nan Chen, Conghao Zhou +4
In this paper, we investigate a radio access network (RAN) slicing problem for Internet of vehicles (IoV) services with different quality of service (QoS) requirements, in which mu…