Publications

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.

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.

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.

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.

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.

Xie, Z., J. Pan, C. C. Chang, R. Liang, E. C. Barboza, and Y. Chen. “Deep Learning for Routability.” In Machine Learning Applications in Electronic Design Automation, 35–61, 2023. https://doi.org/10.1007/978-3-031-13074-8_2.

Zheng, Q., S. Li, Y. Wang, Z. Li, Y. Chen, and H. H. Li. “Accelerating Sparse Attention with a Reconfigurable Non-volatile Processing-In-Memory Architecture.” In Proceedings Design Automation Conference, Vol. 2023-July, 2023. https://doi.org/10.1109/DAC56929.2023.10247908.

Sun, J., Z. Xu, D. Yang, V. Nath, W. Li, C. Zhao, D. Xu, Y. Chen, and H. R. Roth. “Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples.” In Proceedings of the IEEE International Conference on Computer Vision, 5180–89, 2023. https://doi.org/10.1109/ICCV51070.2023.00480.

Li, H. H. “MWSCAS Guest Editorial Special Issue Based on the 64th International Midwest Symposium on Circuits and Systems.” IEEE Transactions on Circuits and Systems I Regular Papers 70, no. 1 (January 1, 2023): 1–2. https://doi.org/10.1109/TCSI.2022.3226647.

Zhang, J., H. Wang, G. S. Ravi, F. T. Chong, S. Han, F. Mueller, and Y. Chen. “DISQ: Dynamic Iteration Skipping for Variational Quantum Algorithms.” In Proceedings 2023 IEEE International Conference on Quantum Computing and Engineering Qce 2023, 1:1062–73, 2023. https://doi.org/10.1109/QCE57702.2023.00120.

Chen, Y. “2023: The Golden Age of Semiconductors.” IEEE Circuits and Systems Magazine 23, no. 1 (January 1, 2023): 3. https://doi.org/10.1109/MCAS.2023.3243685.

Yang, H., H. Yin, M. Shen, P. Molchanov, H. Li, and J. Kautz. “Global Vision Transformer Pruning with Hessian-Aware Saliency.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2023-June:18547–57, 2023. https://doi.org/10.1109/CVPR52729.2023.01779.

Zhang, T., M. Ma, F. Yan, H. Li, and Y. Chen. “: Joint Point Interaction-Dimension Search for 3D Point Cloud.” In Proceedings 2023 IEEE Winter Conference on Applications of Computer Vision Wacv 2023, 1298–1307, 2023. https://doi.org/10.1109/WACV56688.2023.00135.

Sengupta, P., A. Tyagi, Y. Chen, and J. Hu. “Early Identification of Timing Critical RTL Components using ML based Path Delay Prediction.” In 2023 ACM IEEE 5th Workshop on Machine Learning for CAD Mlcad 2023, 2023. https://doi.org/10.1109/MLCAD58807.2023.10299879.

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.