Publications

2022

Li, T., N. Jing, Z. Mao, and Y. Chen. “A Hybrid-Grained Remapping Defense Scheme Against Hard Failures for Row-Column-NVM.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 41, no. 6 (June 1, 2022): 1842–54. https://doi.org/10.1109/TCAD.2021.3097288.

Yang, X., B. Taylor, A. Wu, Y. Chen, and L. O. Chua. “Research Progress on Memristor: From Synapses to Computing Systems.” IEEE Transactions on Circuits and Systems I: Regular Papers 69, no. 5 (May 1, 2022): 1845–57. https://doi.org/10.1109/TCSI.2022.3159153.

Mao, J., Q. Yang, A. Li, K. W. Nixon, H. Li, and Y. Chen. “Toward Efficient and Adaptive Design of Video Detection System with Deep Neural Networks.” ACM Transactions on Embedded Computing Systems 21, no. 3 (May 1, 2022). https://doi.org/10.1145/3484946.

Chen, Y., and Y. Wang. “A survey of architectures of neural network accelerators.” Scientia Sinica Informationis 52, no. 4 (April 1, 2022): 596–611. https://doi.org/10.1360/SSI-2021-0409.

Li, H. H., A. R. Alameldeen, and O. Mutlu. “Guest Editors' Introduction: Near-Memory and In-Memory Processing.” IEEE Design and Test 39, no. 2 (April 1, 2022): 46–47. https://doi.org/10.1109/MDAT.2021.3124742.

Chen, Yiran, and Hai Helen Li. “SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme-Scale Computing Platforms.” Office of Scientific and Technical Information (OSTI), February 26, 2022. https://doi.org/10.2172/1846568.

Chen, Y., and S. Reda. “ISLPED 2021: The 25th Anniversary!.” In IEEE Design and Test, 39:92–93, 2022. https://doi.org/10.1109/MDAT.2021.3128437.

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.

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.

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.

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.

Yang, X., H. Yang, J. Zhang, H. H. Li, and Y. Chen. “On Building Efficient and Robust Neural Network Designs.” In Conference Record - Asilomar Conference on Signals, Systems and Computers, 2022-October:317–21, 2022. https://doi.org/10.1109/IEEECONF56349.2022.10051891.

Cheng, H. P., F. Liang, M. Li, B. Cheng, F. Yan, H. Li, V. Chandra, and Y. Chen. “ScaleNAS: Multi-Path One-Shot NAS for Scale-Aware High-Resolution Representation.” In Proceedings of Machine Learning Research, Vol. 188, 2022.

Zhang, J., Y. Chen, and H. Li. “Privacy Leakage of Adversarial Training Models in Federated Learning Systems.” In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2022-June:107–13, 2022. https://doi.org/10.1109/CVPRW56347.2022.00021.

Gao, Z., M. Tang, A. Li, and Y. Chen. “An Audio Frequency Unfolding Framework for Ultra-Low Sampling Rate Sensors.” In Proceedings - International Symposium on Quality Electronic Design, ISQED, Vol. 2022-April, 2022. https://doi.org/10.1109/ISQED54688.2022.9806149.

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.

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.

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.

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.

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.

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.