Publications

Chandra, V., Y. Chen, and S. Yoo. “Introduction to the Special Section on Energy-Efficient AI Chips.” ACM Transactions on Design Automation of Electronic Systems 27, no. 5 (September 21, 2022). https://doi.org/10.1145/3538502.

Zhang, J., J. Tang, Y. Chen, J. Liu, J. Ye, M. Wolf, V. Narayanan, M. Srivastava, M. I. Jordan, and V. Bahl. “The 5th Artificial Intelligence of Things (AIoT) Workshop.” In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 4912–13, 2022. https://doi.org/10.1145/3534678.3542911.

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.

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.

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.

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.

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.

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.