Publications

Joardar, B. K., J. R. Doppa, H. Li, K. Chakrabarty, and P. P. Pande. “ReaLPrune: ReRAM Crossbar-Aware Lottery Ticket Pruning for CNNs.” IEEE Transactions on Emerging Topics in Computing 11, no. 2 (April 1, 2023): 303–17. https://doi.org/10.1109/TETC.2022.3223630.

Hanson, E., M. Horton, H. H. Li, and Y. Chen. “DefT: Boosting Scalability of Deformable Convolution Operations on GPUs.” In International Conference on Architectural Support for Programming Languages and Operating Systems ASPLOS, 3:134–46, 2023. https://doi.org/10.1145/3582016.3582017.

Hanson, E., S. Li, X. Qian, H. H. Li, and Y. Chen. “DyNNamic: Dynamically Reshaping, High Data-Reuse Accelerator for Compact DNNs.” IEEE Transactions on Computers 72, no. 3 (March 1, 2023): 880–92. https://doi.org/10.1109/TC.2022.3184272.

Augustine, C., and H. Li. “ISLPED 2022: An Experience of a Hybrid Conference in the Time of COVID-19.” IEEE Design and Test 40, no. 1 (February 1, 2023): 105–7. https://doi.org/10.1109/MDAT.2022.3208552.

Pang, Meng, Binghui Wang, Mang Ye, Yiu-Ming Cheung, Yiran Chen, and Bihan Wen. “DisP+V: A Unified Framework for Disentangling Prototype and Variation From Single Sample per Person.” IEEE Transactions on Neural Networks and Learning Systems 34, no. 2 (February 2023): 867–81. https://doi.org/10.1109/tnnls.2021.3103194.

Chang, C. C., J. Pan, Z. Xie, J. Hu, and Y. Chen. “Rethink before Releasing Your Model: ML Model Extraction Attack in EDA.” In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 252–57, 2023. https://doi.org/10.1145/3566097.3567896.

Yang, X., S. Li, Q. Zheng, and Y. Chen. “Improving the Robustness and Efficiency of PIM-Based Architecture by SW/HW Co-Design.” In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 618–23, 2023. https://doi.org/10.1145/3566097.3568358.

Chang, C. C., J. Pan, Z. Xie, Y. Li, Y. Lin, J. Hu, and Y. Chen. “Fully Automated Machine Learning Model Development for Analog Placement Quality Prediction.” In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 58–63, 2023. https://doi.org/10.1145/3566097.3567881.

Zhang, J., A. Muhamed, A. Anantharaman, G. Wang, C. Chen, K. Zhong, Q. Cui, et al. “ReAugKD: Retrieval-Augmented Knowledge Distillation For Pre-trained Language Models.” In Proceedings of the Annual Meeting of the Association for Computational Linguistics, 2:1128–36, 2023. https://doi.org/10.18653/v1/2023.acl-short.97.

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.

Su, Q., A. Netchaev, H. Li, and S. Ji. “FLSL: Feature-level Self-supervised Learning.” In Advances in Neural Information Processing Systems, Vol. 36, 2023.

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.

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.

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.

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.