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.

Yan, B., J. L. Hsu, P. C. Yu, C. C. Lee, Y. Zhang, W. Yue, G. Mei, et al. “A 1.041-Mb/mm227.38-TOPS/W Signed-INT8 Dynamic-Logic-Based ADC-less SRAM Compute-in-Memory Macro in 28nm with Reconfigurable Bitwise Operation for AI and Embedded Applications.” In Digest of Technical Papers IEEE International Solid State Circuits Conference, 2022-February:188–90, 2022. https://doi.org/10.1109/ISSCC42614.2022.9731545.

Zhang, G. L., S. Zhang, H. H. Li, and U. Schlichtmann. “RRAM-based Neuromorphic Computing: Data Representation, Architecture, Logic, and Programming.” In Proceedings 2022 25th Euromicro Conference on Digital System Design Dsd 2022, 423–28, 2022. https://doi.org/10.1109/DSD57027.2022.00063.

Inkawhich, M., N. Inkawhich, E. Davis, H. Li, and Y. Chen. “The Untapped Potential of Off-the-Shelf Convolutional Neural Networks.” In Proceedings 2022 IEEE Cvf Winter Conference on Applications of Computer Vision Wacv 2022, 2907–16, 2022. https://doi.org/10.1109/WACV51458.2022.00296.

Chen, Y., and I. Mohomed. “Message from the Program Co-Chairs: SEC 2022.” In Proceedings 2022 IEEE ACM 7th Symposium on Edge Computing Sec 2022, XV, 2022. https://doi.org/10.1109/SEC54971.2022.00006.

Fan, H., B. Wang, P. Zhou, A. Li, Z. Xu, C. Fu, H. Li, and Y. Chen. “Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs.” In 2021 IEEE 23rd International Conference on High Performance Computing and Communications 7th International Conference on Data Science and Systems 19th International Conference on Smart City and 7th International Conference on Dependability in Sensor Cloud and Big Data Systems and Applications Hpcc Dss Smartcity Dependsys 2021, 933–40, 2022. https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00149.

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.