Xiang Chen

Xiang Chen

Intelligence Fusion Laboratory

Journal Articles

  • [IEEE-TCAD ‘24] * F. Yu, Z. Xu, L. Shangguan, D. Wang, D. Stamoulis, R. Madhok, N. Karianakis, A. Li, C. Liu, Y. Chen, and X. Chen. “Rethinking Latency-Aware DNN Design With GPU Tail Effect Analysis,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, May 2024.
  • [IEEE-TCCN ‘24] * W. Zhang, Y. Wang, X. Chen, L. Liu, and Z. Tian. “Collaborative Learning based Spectrum Sensing under Partial Observations,” IEEE Transactions on Cognitive Communications and Networking, Apr. 2024.
  • [IEEE-TNNLS ‘23] * P. Xu, Y. Wang, X. Chen, and Z. Tian. “QC-ODKLA: Quantized and Communication-Censored Online Decentralized Kernel Learning via Linearized ADMM,” IEEE Transactions on Neural Networks and Learning Systems, Sep. 2023.
  • [IEEE-TC ‘22] † Z. Xu, F. Yu, J. Xiong, and X. Chen. “HeliosX: Heterogeneity-Aware Federated Learning for Dynamic Edge Collaboration Management,” IEEE Transactions on Computers, to appear.
  • [IEEE-TC ‘22] † F. Yu, W. Zhang, Z. Qin, Z. Xu, D. Wang, C. Liu, Z. Tian, and X. Chen. “Fed$^2$X: Feature-Aligned Large-Scale Federated Learning Systems,” IEEE Transactions on Computers, to appear.
  • [HPC ‘22] † F. Yu, Z. Xu, Z. Qin, and X. Chen. “Privacy-Preserving Federated Learning for Transportation Mode Prediction based on Personal Mobility Data,” High-Confidence Computing, Dec. 2022.
  • [ACM-TECS ‘22] † Z. Xu, F. Yu, and X. Chen. “LanCeX: A Versatile and Lightweight Defense Method against Condensed Adversarial Attacks,” ACM Transactions on Embedded Computing Systems, Aug. 2022.
  • [IEEE-TCAD ‘22] † F. Yu, C. Liu, D. Wang, Y. Wang and X. Chen. “AntiDoteX: Attention-based Neural Network Runtime Efficiency Dynamic Optimization,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Jan. 2022.
  • [JMLR ‘21] * P. Xu, Y. Wang, X. Chen, and Z. Tian. “COKE: Communication-Censored Decentralized Kernel Learning,” Journal of Machine Learning Research, Vol. 22 No. 196, pp. 1~35, Oct. 2021.
  • [IEEE-TCAD ‘21] † Z. Qin, F. Yu, Z. Xu, C. Liu, and X. Chen. “CaptorX: A Class-Adaptive Convolutional Neural Network Reconfiguration Framework,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Feb. 2021.
  • [IEEE-TCAD ‘20] † F. Yu, Z. Qin, C. Liu, D. Wang, and X. Chen. “REIN the RobuTS: Robust DNN-based Image Recognition in Autonomous Driving Systems,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Oct. 2020.
  • [IEEE-TCAD ‘20] † Z. Xu, F. Yu, C. Liu, and X. Chen. “DiReCtX: Dynamic Resource-Aware CNN Reconfiguration Framework for Real-Time Mobile Application,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, May 2020.
  • [GMU-JSSR ‘19] † R. Yu, L. Punya, K. Wang, Z. Qin, and X. Chen. “CAPTURE: An End-to-End Mobile Implementation for a Computationally Optimized Deep Learning Framework,” Journal of Student-Scientists’ Research, George Mason University, Nov. 2019.
  • [AMC-MFC ‘18] † Z. Qin, F. Yu, C. Liu, and X. Chen. “How Convolutional Neural Networks See the World — A Survey of Convolutional Neural Network Visualization Methods,” Advances in Mathematics of Communications Journal on Mathematical Foundations of Computing, Vol. 1, Iss. 2, No. 149, pp. 149~180, May 2018.
  • [ACM-ETCS ‘12] Z. Sun, X. Chen, Y. Zhang, H. Li, and Y. Chen. “Non-volatile Memories as the Data Storage System for Implantable ECG Recorder,” ACM Journal on Emerging Technologies in Computing Systems, Vol. 8, Iss. 2, No. 13, pp. 1~16, Jun. 2012.