Chengxi Li

Orcid: 0000-0003-1649-1943

Affiliations:
  • Tsinghua University, Department of Electronic Engineering, Beijing, China


According to our database1, Chengxi Li authored at least 17 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Distributed Learning Based on 1-Bit Gradient Coding in the Presence of Stragglers.
IEEE Trans. Commun., August, 2024

Decentralized Learning Based on Gradient Coding With Compressed Communication.
IEEE Trans. Signal Process., 2024

Robust Cross-Modal Remote Sensing Image Retrieval via Maximal Correlation Augmentation.
IEEE Trans. Geosci. Remote. Sens., 2024

COMIC: An unsupervised change detection method for heterogeneous remote sensing images based on copula mixtures and Cycle-Consistent Adversarial Networks.
Inf. Fusion, 2024

2023
A Copula-Based Method for Change Detection With Multisensor Optical Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2023

HGR Maximal Correlation Augmented Cross-Modal Remote Sensing Retrieval.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022
Robust Federated Opportunistic Learning in the Presence of Label Quality Disparity.
IEEE Internet Things J., 2022

Federated Learning With Soft Clustering.
IEEE Internet Things J., 2022

Decentralized Federated Learning via Mutual Knowledge Transfer.
IEEE Internet Things J., 2022

Distributed detection of sparse signals with censoring sensors in clustered sensor networks.
Inf. Fusion, 2022

2021
Communication-Efficient Federated Learning Based on Compressed Sensing.
IEEE Internet Things J., 2021

2020
Distributed Detection of Sparse Signals With Physical Layer Secrecy Constraints: A Falsified Censoring Strategy.
IEEE Trans. Signal Process., 2020

Distributed Detection of Sparse Stochastic Signals With 1-Bit Data in Tree-Structured Sensor Networks.
IEEE Trans. Signal Process., 2020

Distributed Detection of Sparse Signals With Censoring Sensors Via Locally Most Powerful Test.
IEEE Signal Process. Lett., 2020

Distributed Detection of Sparse Signals with 1-Bit Data in Two-Level Two-Degree Tree-Structured Sensor Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Secure Distributed Detection of Sparse Signals via Falsification of Local Compressive Measurements.
IEEE Trans. Signal Process., 2019

Distributed Detection of Sparse Stochastic Signals via Fusion of 1-bit Local Likelihood Ratios.
IEEE Signal Process. Lett., 2019


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