14 citations · 20 across the 24 of their papers we have counts for
4 papers · 1 filter
Byzantine-Robust and Communication-Efficient Distributed Training: Compressive and Cyclic Gradient Coding
Chengxi Li, Youssef Allouah, Rachid Guerraoui +2
In this paper, we study the problem of distributed training (DT) under Byzantine attacks with communication constraints. While prior work has developed various robust aggregation r…
Biased Compression in Gradient Coding for Distributed Learning
Chengxi Li, Ming Xiao, Mikael Skoglund
Communication bottlenecks and the presence of stragglers pose significant challenges in distributed learning (DL). To deal with these challenges, recent advances leverage unbiased…
On Resilient and Efficient Linear Secure Aggregation in Hierarchical Federated Learning
Shudi Weng, Xiang Zhang, Yizhou Zhao +3
In this paper, we study the fundamental limits of hierarchical secure aggregation under unreliable communication. We consider a hierarchical network where each client connects to m…
Cooperative Gradient Coding
Shudi Weng, Ming Xiao, Chao Ren +1
This work studies gradient coding (GC) in the context of distributed training problems with unreliable communication. We propose cooperative GC (CoGC), a novel gradient-sharing-bas…