Publications

Li, Z., Q. Zheng, B. Yan, R. Huang, B. Li, and Y. Chen. “ASTERS: Adaptable Threshold Spike-timing Neuromorphic Design with Twin-Column ReRAM Synapses.” In Proceedings - Design Automation Conference, 1099–1104, 2022. https://doi.org/10.1145/3489517.3530591.

Yang, H., X. Yang, N. Z. Gong, and Y. Chen. “HERO: Hessian-Enhanced Robust Optimization for Unifying and Improving Generalization and Quantization Performance.” In Proceedings - Design Automation Conference, 25–30, 2022. https://doi.org/10.1145/3489517.3530678.

Pan, J., C. C. Chang, Z. Xie, A. Li, M. Tang, T. Zhang, J. Hu, and Y. Chen. “Towards Collaborative Intelligence: Routability Estimation based on Decentralized Private Data.” In Proceedings - Design Automation Conference, 961–66, 2022. https://doi.org/10.1145/3489517.3530578.

Hanson, E., S. Li, H. H. Li, and Y. Chen. “Cascading Structured Pruning: Enabling High Data Reuse for Sparse DNN Accelerators.” In Proceedings - International Symposium on Computer Architecture, 522–35, 2022. https://doi.org/10.1145/3470496.3527419.

Taylor, B., Q. Zheng, Z. Li, S. Li, and Y. Chen. “Processing-in-Memory Technology for Machine Learning: From Basic to ASIC.” IEEE Transactions on Circuits and Systems II: Express Briefs 69, no. 6 (June 1, 2022): 2598–2603. https://doi.org/10.1109/TCSII.2022.3168404.

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.

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.

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.

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.

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.

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.

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.