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