Publications

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.

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, 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.

Song, L., F. Chen, H. Li, and Y. Chen. “Refloat: Low-Cost Floating-Point Processing in ReRAM for Accelerating Iterative Linear Solvers.” In International Conference for High Performance Computing, Networking, Storage and Analysis, SC, 2023. https://doi.org/10.1145/3581784.3607077.

Yang, Y., H. Li, and Y. Chen. “Stable and Causal Inference for Discriminative Self-supervised Deep Visual Representations.” In Proceedings of the IEEE International Conference on Computer Vision, 16063–74, 2023. https://doi.org/10.1109/ICCV51070.2023.01476.

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.

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.

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.