Publications

2023

Zhang, J., N. Inkawhich, R. Linderman, Y. Chen, and H. Li. “Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environments.” In Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023, 5520–29, 2023. https://doi.org/10.1109/WACV56688.2023.00549.

Wu, C., X. Yang, Y. Chen, and M. Li. “Photonic Bayesian Neural Network Using Programmed Optical Noises.” IEEE Journal of Selected Topics in Quantum Electronics 29, no. 2 (January 1, 2023). https://doi.org/10.1109/JSTQE.2022.3217819.

Kim, B., Z. Du, J. Sun, and Y. Chen. “Invited Paper: Towards the Efficiency, Heterogeneity, and Robustness of Edge AI.” In IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, 2023. https://doi.org/10.1109/ICCAD57390.2023.10323922.

Petri, R., G. L. Zhang, Y. Chen, U. Schlichtmann, and B. Li. “PowerPruning: Selecting Weights and Activations for Power-Efficient Neural Network Acceleration.” In Proceedings - Design Automation Conference, Vol. 2023-July, 2023. https://doi.org/10.1109/DAC56929.2023.10247868.

Tung, C. H., B. K. Joardar, P. P. Pande, J. R. Doppa, H. H. Li, and K. Chakrabarty. “Dynamic Task Remapping for Reliable CNN Training on ReRAM Crossbars.” In Proceedings -Design, Automation and Test in Europe, DATE, Vol. 2023-April, 2023. https://doi.org/10.23919/DATE56975.2023.10137238.

Hu, S., Y. Chen, Q. Zhu, and A. W. Colombo. “Guest Editorial Machine Learning for Resilient Industrial Cyber-Physical Systems.” IEEE Transactions on Automation Science and Engineering 20, no. 1 (January 1, 2023): 3–4. https://doi.org/10.1109/TASE.2022.3223583.

Linderman, R., J. Zhang, N. Inkawhich, H. Li, and Y. Chen. “FINE-GRAIN INFERENCE ON OUT-OF-DISTRIBUTION DATA WITH HIERARCHICAL CLASSIFICATION.” In Proceedings of Machine Learning Research, 232:162–83, 2023.

Zhang, J., A. Li, M. Tang, J. Sun, X. Chen, F. Zhang, C. Chen, Y. Chen, and H. Li. “Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction.” In Proceedings of Machine Learning Research, 202:41354–81, 2023.

Qiao, X., and H. Li. “On a New Type of Neural Computation for Probabilistic Symbolic Reasoning.” In Proceedings of the International Joint Conference on Neural Networks, Vol. 2023-June, 2023. https://doi.org/10.1109/IJCNN54540.2023.10191306.

Zhang, L., Y. Chen, A. Li, B. Wang, F. Li, J. Cao, and B. Niu. “Interpreting Disparate Privacy-Utility Tradeoff in Adversarial Learning via Attribute Correlation.” In Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023, 4690–98, 2023. https://doi.org/10.1109/WACV56688.2023.00468.

Wolters, C., B. Taylor, E. Hanson, X. Yang, U. Schlichtmann, and Y. Chen. “Biologically Plausible Learning on Neuromorphic Hardware Architectures.” In Midwest Symposium on Circuits and Systems, 733–37, 2023. https://doi.org/10.1109/MWSCAS57524.2023.10405905.

2022

Shafique, M., T. Theocharides, H. Li, and C. Jason Xue. “Introduction to the Special Issue on Accelerating AI on the Edge - Part 2.” ACM Transactions on Embedded Computing Systems 21, no. 6 (December 12, 2022). https://doi.org/10.1145/3563127.

Du, Z., J. Sun, A. Li, P. Y. Chen, J. Zhang, H. Li, and Y. Chen. “Rethinking normalization methods in federated learning.” In DistributedML 2022 - Proceedings of the 3rd International Workshop on Distributed Machine Learning, Part of CoNEXT 2022, 16–22, 2022. https://doi.org/10.1145/3565010.3569062.

Liu, F., W. Zhao, Z. Wang, Y. Zhao, T. Yang, Y. Chen, and L. Jiang. “IVQ: In-Memory Acceleration of DNN Inference Exploiting Varied Quantization.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 41, no. 12 (December 1, 2022): 5313–26. https://doi.org/10.1109/TCAD.2022.3156017.

Zheng, Q., X. Li, Y. Guan, Z. Wang, Y. Cai, Y. Chen, G. Sun, and R. Huang. “PIMulator-NN: An Event-Driven, Cross-Level Simulation Framework for Processing-In-Memory-Based Neural Network Accelerators.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 41, no. 12 (December 1, 2022): 5464–75. https://doi.org/10.1109/TCAD.2022.3160947.

Li, H. H. “Guest Editorial Special Issue on the International Symposium on Integrated Circuits and Systems - ISICAS 2022.” IEEE Transactions on Circuits and Systems I: Regular Papers 69, no. 12 (December 1, 2022): 4730. https://doi.org/10.1109/TCSI.2022.3219319.

Li, T., N. Jing, J. Jiang, Q. Wang, Z. Mao, and Y. Chen. “A Novel Architecture Design for Output Significance Aligned Flow with Adaptive Control in ReRAM-based Neural Network Accelerator.” ACM Transactions on Design Automation of Electronic Systems 27, no. 6 (November 22, 2022). https://doi.org/10.1145/3510819.

Hu, S., S. Yu, H. Li, and V. Piuri. “Guest Editorial Special Issue on Security, Privacy, and Trustworthiness in Intelligent Cyber-Physical Systems and Internet of Things.” IEEE Internet of Things Journal 9, no. 22 (November 15, 2022): 22044–47. https://doi.org/10.1109/JIOT.2022.3207335.

Chen, X., D. Li, Y. Chen, and J. Xiong. “Boosting the sensing granularity of acoustic signals by exploiting hardware non-linearity.” In HotNets 2022 - Proceedings of the 2022 21st ACM Workshop on Hot Topics in Networks, 53–59, 2022. https://doi.org/10.1145/3563766.3564091.

Sun, J., A. Li, L. Duan, S. Alam, X. Deng, X. Guo, H. Wang, et al. “FedSEA: A Semi-Asynchronous Federated Learning Framework for Extremely Heterogeneous Devices.” In SenSys 2022 - Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems, 106–19, 2022. https://doi.org/10.1145/3560905.3568538.

Ogbogu, C., A. I. Arka, B. K. Joardar, J. R. Doppa, H. Li, K. Chakrabarty, and P. P. Pande. “Accelerating Large-Scale Graph Neural Network Training on Crossbar Diet.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 41, no. 11 (November 1, 2022): 3626–37. https://doi.org/10.1109/TCAD.2022.3197342.

Xie, Z., R. Liang, X. Xu, J. Hu, C. C. Chang, J. Pan, and Y. Chen. “Preplacement Net Length and Timing Estimation by Customized Graph Neural Network.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 41, no. 11 (November 1, 2022): 4667–80. https://doi.org/10.1109/TCAD.2022.3149977.

Chen, Y., and Q. Qiu. “Guest Editorial: IEEE TC Special Issue on Software, Hardware and Applications for Neuromorphic Computing.” IEEE Transactions on Computers 71, no. 11 (November 1, 2022): 2705–6. https://doi.org/10.1109/TC.2022.3208389.

Henkel, J., H. Li, A. Raghunathan, M. B. Tahoori, S. Venkataramani, X. Yang, and G. Zervakis. “Approximate computing and the efficient machine learning expedition.” In IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, 2022. https://doi.org/10.1145/3508352.3561105.

Pan, J., C. C. Chang, Z. Xie, J. Hu, and Y. Chen. “Robustify ML-based lithography hotspot detectors.” In IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, 2022. https://doi.org/10.1145/3508352.3549389.