Publications

2023

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.

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.

Pan, J., X. Lin, J. Xu, Y. Chen, and C. Zhuo. “Lithography Hotspot Detection Based on Heterogeneous Federated Learning with Local Adaptation and Feature Selection.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, January 1, 2023. https://doi.org/10.1109/TCAD.2023.3332841.

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.

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.

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.

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.

Gopal, B., A. Sridhar, T. Zhang, and Y. Chen. “LISSNAS: Locality-based Iterative Search Space Shrinkage for Neural Architecture Search.” In IJCAI International Joint Conference on Artificial Intelligence, 2023-August:773–81, 2023.

Kim, B., S. Li, and H. Li. “INCA: Input-stationary Dataflow at Outside-the-box Thinking about Deep Learning Accelerators.” In Proceedings - International Symposium on High-Performance Computer Architecture, 2023-February:29–41, 2023. https://doi.org/10.1109/HPCA56546.2023.10070992.

Zhang, Q., S. Li, G. Zhou, J. Pan, C. C. Chang, Y. Chen, and Z. Xie. “PANDA: Architecture-Level Power Evaluation by Unifying Analytical and Machine Learning Solutions.” In IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, 2023. https://doi.org/10.1109/ICCAD57390.2023.10323665.

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.

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.