Lixing Yu

Orcid: 0000-0003-0333-2476

According to our database1, Lixing Yu authored at least 28 papers between 2018 and 2025.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
SpikingViT: A Multiscale Spiking Vision Transformer Model for Event-Based Object Detection.
IEEE Trans. Cogn. Dev. Syst., February, 2025

FedELR: When federated learning meets learning with noisy labels.
Neural Networks, 2025

Probabilistic Semantics Guided Discovery of Approximate Functional Dependencies.
Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Improving Graph Contrastive Learning with Community Structure.
Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Time-independent Spiking Neuron via Membrane Potential Estimation for Efficient Spiking Neural Networks.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024
Efficient Federated Learning With Channel Status Awareness and Devices' Personal Touch.
IEEE Trans. Mob. Comput., December, 2024

Anomaly Detection for Multivariate Time Series with Multi-scale Feature Interactions.
Proceedings of the Database Systems for Advanced Applications, 2024

FedLTF: Linear Probing Teaches Fine-tuning to Mitigate Noisy Labels in Federated Learning.
Proceedings of the Asian Conference on Machine Learning, 2024

2022
Energy-Efficient Computation Offloading in Mobile Edge Computing Systems With Uncertainties.
IEEE Trans. Wirel. Commun., 2022

Energy-Efficient Computation Offloading in MobileEdge Computing Systems with Uncertainties.
CoRR, 2022

An Anomaly Detection System for Transparent Objects Using Polarized-Image Fusion Technique.
Proceedings of the IEEE Sensors Applications Symposium, 2022

2021
STEP: A Spatio-Temporal Fine-Granular User Traffic Prediction System for Cellular Networks.
IEEE Trans. Mob. Comput., 2021

Deep Q-Network-Based Feature Selection for Multisourced Data Cleaning.
IEEE Internet Things J., 2021

Weak Signal Detection in 5G+ Systems: A Distributed Deep Learning Framework.
Proceedings of the MobiHoc '21: The Twenty-second International Symposium on Theory, 2021

2020
Unsupervised Anomaly Detection in IoT Systems for Smart Cities.
IEEE Trans. Netw. Sci. Eng., 2020

Earthquake Prediction Based on Spatio-Temporal Data Mining: An LSTM Network Approach.
IEEE Trans. Emerg. Top. Comput., 2020

Community Detection in Online Social Networks: A Differentially Private and Parsimonious Approach.
IEEE Trans. Comput. Soc. Syst., 2020

Spectrum Availability Prediction for Cognitive Radio Communications: A DCG Approach.
IEEE Trans. Cogn. Commun. Netw., 2020

AI at the Edge: Blockchain-Empowered Secure Multiparty Learning With Heterogeneous Models.
IEEE Internet Things J., 2020

TrafficChain: A Blockchain-Based Secure and Privacy-Preserving Traffic Map.
IEEE Access, 2020

2019
Learning to Learn Gradient Aggregation by Gradient Descent.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Quantized Adversarial Training: An Iterative Quantized Local Search Approach.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

PerRNN: Personalized Recurrent Neural Networks for Acceleration-Based Human Activity Recognition.
Proceedings of the 2019 IEEE International Conference on Communications, 2019

Exploring Spatial-Temporal Patterns From Individual User Cellular Traffic.
Proceedings of the 2019 IEEE International Symposium on Dynamic Spectrum Access Networks, 2019

2018
Cross-Domain Sentiment Classification via a Bifurcated-LSTM.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Online Power Control for 5G Wireless Communications: A Deep Q-Network Approach.
Proceedings of the 2018 IEEE International Conference on Communications, 2018

Multidimensional Time Series Anomaly Detection: A GRU-based Gaussian Mixture Variational Autoencoder Approach.
Proceedings of The 10th Asian Conference on Machine Learning, 2018

SecureNets: Secure Inference of Deep Neural Networks on an Untrusted Cloud.
Proceedings of The 10th Asian Conference on Machine Learning, 2018


  Loading...