Qing Xu

According to our database, Qing Xu authored at least 8 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Reinforced Knowledge Distillation for Time Series Regression.

Qing Xu, Keyu Wu, Min Wu, Kezhi Mao, Xiaoli Li, Zhenghua Chen

IEEE Trans. Artif. Intell., June, 2024

LLM-based Knowledge Pruning for Time Series Data Analytics on Edge-computing Devices.

Ruibing Jin, Qing Xu, Min Wu, Yuecong Xu, Dan Li, Xiaoli Li, Zhenghua Chen

CoRR, 2024

From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks.

Xue Geng, Zhe Wang, Chunyun Chen, Qing Xu, Kaixin Xu, Chao Jin, Manas Gupta, Xulei Yang, Zhenghua Chen, Mohamed M. Sabry Aly, Jie Lin, Min Wu, Xiaoli Li

CoRR, 2024

Improve Knowledge Distillation via Label Revision and Data Selection.

Weichao Lan, Yiu-ming Cheung, Qing Xu, Buhua Liu, Zhikai Hu, Mengke Li, Zhenghua Chen

CoRR, 2024

2023

A Hybrid Ensemble Deep Learning Approach for Early Prediction of Battery Remaining Useful Life.

Qing Xu, Min Wu, Edwin Khoo, Zhenghua Chen, Xiaoli Li

IEEE CAA J. Autom. Sinica, 2023

Distilling Universal and Joint Knowledge for Cross-Domain Model Compression on Time Series Data.

Qing Xu, Min Wu, Xiaoli Li, Kezhi Mao, Zhenghua Chen

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

KDnet-RUL: A Knowledge Distillation Framework to Compress Deep Neural Networks for Machine Remaining Useful Life Prediction.

Qing Xu, Zhenghua Chen, Keyu Wu, Chao Wang, Min Wu, Xiaoli Li

IEEE Trans. Ind. Electron., 2022

Contrastive adversarial knowledge distillation for deep model compression in time-series regression tasks.

Qing Xu, Zhenghua Chen, Mohamed Ragab, Chao Wang, Min Wu, Xiaoli Li

Neurocomputing, 2022