activity
20192026
most citedDecentralized Federated Learning via Mutual Knowledge Transfer

127 citations · 145 across the 8 of their papers we have counts for

collaborators

9 papers

cs.IR2026

Uncertainty-Aware Cross-Modal Remote Sensing Image-Text Retrieval via Evidential Learning

Zhuoyue Wang, Xueqian Wang, Gang Li +3

In cross-modal remote sensing image-text retrieval (CMRSITR), test-time remote sensing (RS) images and textual descriptions may deviate from well-curated benchmark conditions due t…

cs.LG2025

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…

eess.SP2024

Supplementary File: Cooperative Gradient Coding for Semi-Decentralized Federated Learning

Shudi Weng, Chengxi Li, Ming Xiao +1

Stragglers' effects are known to degrade FL performance. In this paper, we investigate federated learning (FL) over wireless networks in the presence of communication stragglers, w…

cs.LG2024

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…

eess.SP2024

Adaptive Coded Federated Learning: Privacy Preservation and Straggler Mitigation

Chengxi Li, Ming Xiao, Mikael Skoglund

In this article, we address the problem of federated learning in the presence of stragglers. For this problem, a coded federated learning framework has been proposed, where the cen…

cs.LG2024

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…

eess.IV2023

COMIC: An Unsupervised Change Detection Method for Heterogeneous Remote Sensing Images Based on Copula Mixtures and Cycle-Consistent Adversarial Networks

Chengxi Li, Gang Li, Zhuoyue Wang +2

In this paper, we consider the problem of change detection (CD) with two heterogeneous remote sensing (RS) images. For this problem, an unsupervised change detection method has bee…

cs.LG2020★ 127 cited

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…

eess.SP2019★ 18 cited

Distributed Detection of Sparse Stochastic Signals via Fusion of 1-bit Local Likelihood Ratios

Chengxi Li, You He, Xueqian Wang +2

In this letter, we consider the detection of sparse stochastic signals with sensor networks (SNs), where the fusion center (FC) collects 1-bit data from the local sensors and then…