Publications

Zhang, J., Z. Du, J. Sun, A. Li, M. Tang, Y. Wu, Z. Gao, M. Kuo, H. H. Li, and Y. Chen. “Next Generation Federated Learning for Edge Devices: An Overview.” In Proceedings 2022 IEEE 8th International Conference on Collaboration and Internet Computing Cic 2022, 10–15, 2022. https://doi.org/10.1109/CIC56439.2022.00012.

Taylor, B., N. Ramos, E. Yeats, and H. Li. “CMOS Implementation of Spiking Equilibrium Propagation for Real-Time Learning.” In Proceeding IEEE International Conference on Artificial Intelligence Circuits and Systems Aicas 2022, 283–86, 2022. https://doi.org/10.1109/AICAS54282.2022.9869989.

Chen, C., J. Duan, Y. Chen, J. Zhang, S. D. Tran, Y. Xu, L. Chen, B. Zeng, and T. Chilimbi. “Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective.” In Advances in Neural Information Processing Systems, Vol. 35, 2022.

Gao, Z., A. Li, D. Li, J. Liu, J. Xiong, Y. Wang, B. Li, and Y. Chen. “MOM: Microphone based 3D Orientation Measurement.” In Proceedings 21st ACM IEEE International Conference on Information Processing in Sensor Networks IPSN 2022, 132–44, 2022. https://doi.org/10.1109/IPSN54338.2022.00018.

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.

Wu, Changming, Xiaoxuan Yang, Heshan Yu, Ruoming Peng, Ichiro Takeuchi, Yiran Chen, and Mo Li. “Harnessing optoelectronic noises in a photonic generative network.” Science Advances 8, no. 3 (January 2022): eabm2956. https://doi.org/10.1126/sciadv.abm2956.

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.

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.

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.

Li, B., H. Lv, Y. Wang, and Y. Chen. “Security Threat to the Robustness of RRAM-based Neuromorphic Computing System.” In Proceedings 2022 IEEE International Symposium on Smart Electronic Systems Ises 2022, 267–71, 2022. https://doi.org/10.1109/iSES54909.2022.00061.

Inkawhich, N., J. Zhang, E. K. Davis, R. Luley, and Y. Chen. “Improving Out-of-Distribution Detection by Learning from the Deployment Environment.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15 (January 1, 2022): 2070–86. https://doi.org/10.1109/JSTARS.2022.3146362.

Feng, G., B. Kim, and H. H. Li. “Bionic Robust Memristor-Based Artificial Nociception System for Robotics.” In Proceedings IEEE International Symposium on Circuits and Systems, 2022-May:3552–56, 2022. https://doi.org/10.1109/ISCAS48785.2022.9937461.

Wang, B., A. Li, M. Pang, H. Li, and Y. Chen. “GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs.” In Proceedings IEEE International Conference on Data Mining Icdm, 2022-November:498–507, 2022. https://doi.org/10.1109/ICDM54844.2022.00060.

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.

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.

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.

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.

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.

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.