Publications

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. https://doi.org/10.24963/ijcai.2023/86.

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. 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.

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.

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.