127 citations · 145 across the 8 of their papers we have counts for
4 papers · 1 filter
Coded Robust Aggregation for Distributed Learning under Byzantine Attacks
Chengxi Li, Ming Xiao, Mikael Skoglund
In this paper, we investigate the problem of distributed learning (DL) in the presence of Byzantine attacks. For this problem, various robust bounded aggregation (RBA) rules have b…
Distributed Learning based on 1-Bit Gradient Coding in the Presence of Stragglers
Chengxi Li, Mikael Skoglund
This paper considers the problem of distributed learning (DL) in the presence of stragglers. For this problem, DL methods based on gradient coding have been widely investigated, wh…
Gradient Coding in Decentralized Learning for Evading Stragglers
Chengxi Li, Mikael Skoglund
In this paper, we consider a decentralized learning problem in the presence of stragglers. Although gradient coding techniques have been developed for distributed learning to evade…
Decentralized Federated Learning via Mutual Knowledge Transfer
Chengxi Li, Gang Li, Pramod K. Varshney
In this paper, we investigate the problem of decentralized federated learning (DFL) in Internet of things (IoT) systems, where a number of IoT clients train models collectively for…