Publications

2022

Yeats, E., F. Liu, D. Womble, and H. Li. “NashAE: Disentangling Representations Through Adversarial Covariance Minimization,” 13687 LNCS:36–51, 2022. https://doi.org/10.1007/978-3-031-19812-0_3.

Zhang, J., Y. Chen, and J. Chen. “Join-Chain Network: A Logical Reasoning View of the Multi-head Attention in Transformer.” In IEEE International Conference on Data Mining Workshops, ICDMW, 2022-November:947–57, 2022. https://doi.org/10.1109/ICDMW58026.2022.00123.

Lin, X., J. Pan, J. Xu, Y. Chen, and C. Zhuo. “Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation.” In Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC, 2022-January:166–71, 2022. https://doi.org/10.1109/ASP-DAC52403.2022.9712491.

Zhang, Youhui, Yiran Chen, and Yuanyuan Mi. “Editorial: Machine learning for computational neural modeling and data analyses.” Frontiers in Computational Neuroscience 16 (January 2022): 978192. https://doi.org/10.3389/fncom.2022.978192.

Tang, M., X. Ning, Y. Wang, J. Sun, H. Li, and Y. Chen. “FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2022-June:10092–101, 2022. https://doi.org/10.1109/CVPR52688.2022.00986.

2021

Fang, H., B. Taylor, Z. Li, Z. Mei, H. H. Li, and Q. Qiu. “Neuromorphic Algorithm-hardware Codesign for Temporal Pattern Learning.” In Proceedings - Design Automation Conference, 2021-December:361–66, 2021. https://doi.org/10.1109/DAC18074.2021.9586133.

Huang, T., Y. Chen, Z. Zeng, and L. Chua. “Editorial Special Issue for 50th Birthday of Memristor Theory and Application of Neuromorphic Computing Based on Memristor - Part II.” IEEE Transactions on Circuits and Systems I: Regular Papers 68, no. 12 (December 1, 2021): 4835–36. https://doi.org/10.1109/TCSI.2021.3124407.

Li, A., J. Sun, X. Zeng, M. Zhang, H. Li, and Y. Chen. “FedMask: Joint Computation and Communication-Efficient Personalized Federated Learning via Heterogeneous Masking.” In SenSys 2021 - Proceedings of the 2021 19th ACM Conference on Embedded Networked Sensor Systems, 42–55, 2021. https://doi.org/10.1145/3485730.3485929.

Wen, S., W. Liu, Y. Yang, P. Zhou, Z. Guo, Z. Yan, Y. Chen, and T. Huang. “Multilabel Image Classification via Feature/Label Co-Projection.” IEEE Transactions on Systems, Man, and Cybernetics: Systems 51, no. 11 (November 1, 2021): 7250–59. https://doi.org/10.1109/TSMC.2020.2967071.

Huang, T., Y. Chen, Z. Zeng, and L. Chua. “Editorial Special Issue for 50th Birthday of Memristor Theory and Application of Neuromorphic Computing Based on Memristor - Part i.” IEEE Transactions on Circuits and Systems I: Regular Papers 68, no. 11 (November 1, 2021): 4417–18. https://doi.org/10.1109/TCSI.2021.3115842.

Joardar, Biresh Kumar, Janardhan Rao Doppa, Hai Li, Krishnendu Chakrabarty, and Partha Pratim Pande. “Learning to Train CNNs on Faulty ReRAM-based Manycore Accelerators.” ACM Transactions on Embedded Computing Systems 20, no. 5s (October 31, 2021): 1–23. https://doi.org/10.1145/3476986.

Li, S., E. Hanson, X. Qian, H. H. Li, and Y. Chen. “ESCALATE: Boosting the efficiency of sparse CNN accelerator with kernel decomposition.” In Proceedings of the Annual International Symposium on Microarchitecture, MICRO, 992–1004, 2021. https://doi.org/10.1145/3466752.3480043.

Xie, Z., X. Xu, M. Walker, J. Knebel, K. Palaniswamy, N. Hebert, J. Hu, H. Yang, Y. Chen, and S. Das. “APOLLO: An automated power modeling framework for runtime power introspection in high-volume commercial microprocessors.” In Proceedings of the Annual International Symposium on Microarchitecture, MICRO, 1–14, 2021. https://doi.org/10.1145/3466752.3480064.

Yang, Q., J. Mao, Z. Wang, and L. Hai. “Dynamic Regularization on Activation Sparsity for Neural Network Efficiency Improvement.” ACM Journal on Emerging Technologies in Computing Systems 17, no. 4 (October 1, 2021). https://doi.org/10.1145/3447776.

Chen, Y., Q. Qiu, and Y. Lin. “Introduction to the Special Issue on Hardware and Algorithms for Efficient Machine Learning-Part 2.” ACM Journal on Emerging Technologies in Computing Systems 17, no. 4 (October 1, 2021). https://doi.org/10.1145/3464917.

Wang, B., J. Guo, A. Li, Y. Chen, and H. Li. “Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective.” In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1667–76, 2021. https://doi.org/10.1145/3447548.3467273.

Wang, Tao, Patrick Koch, Brett Wujek, Jun Liu, and Hai Li. “The Fifth International Workshop on Automation in Machine Learning.” In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. ACM, 2021. https://doi.org/10.1145/3447548.3469452.

Yang, C., L. Ding, Y. Chen, and H. Li. “Defending against GAN-based DeepFake Attacks via Transformation-aware Adversarial Faces.” In Proceedings of the International Joint Conference on Neural Networks, Vol. 2021-July, 2021. https://doi.org/10.1109/IJCNN52387.2021.9533868.

Mao, J., H. Yang, A. Li, H. Li, and Y. Chen. “TPrune: Efficient Transformer Pruning for Mobile Devices.” ACM Transactions on Cyber-Physical Systems 5, no. 3 (July 1, 2021). https://doi.org/10.1145/3446640.

Zhang, J., Y. Huang, H. Yang, M. Martinez, G. Hickman, J. Krolik, and H. Li. “Efficient FPGA Implementation of a Convolutional Neural Network for Radar Signal Processing.” In 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021, 2021. https://doi.org/10.1109/AICAS51828.2021.9458573.

Chai, X., X. Zhi, Z. Gan, Y. Zhang, Y. Chen, and J. Fu. “Combining improved genetic algorithm and matrix semi-tensor product (STP) in color image encryption.” Signal Processing 183 (June 1, 2021). https://doi.org/10.1016/j.sigpro.2021.108041.

Hu, W., C. H. Chang, A. Sengupta, S. Bhunia, R. Kastner, and H. Li. “An Overview of Hardware Security and Trust: Threats, Countermeasures, and Design Tools.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 40, no. 6 (June 1, 2021): 1010–38. https://doi.org/10.1109/TCAD.2020.3047976.

Wen, S., M. Dong, Y. Yang, P. Zhou, T. Huang, and Y. Chen. “End-to-End Detection-Segmentation System for Face Labeling.” IEEE Transactions on Emerging Topics in Computational Intelligence 5, no. 3 (June 1, 2021): 457–67. https://doi.org/10.1109/TETCI.2019.2947319.

Li, A., J. Guo, H. Yang, F. D. Salim, and Y. Chen. “DeepObfuscator: Obfuscating Intermediate Representations with Privacy-Preserving Adversarial Learning on Smartphones.” In IoTDI 2021 - Proceedings of the 2021 International Conference on Internet-of-Things Design and Implementation, 28–39, 2021. https://doi.org/10.1145/3450268.3453519.

Joardar, B. K., J. R. Doppa, P. P. Pande, H. Li, and K. Chakrabarty. “AccuReD: High Accuracy Training of CNNs on ReRAM/GPU Heterogeneous 3-D Architecture.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 40, no. 5 (May 1, 2021): 971–84. https://doi.org/10.1109/TCAD.2020.3013194.