| Exponential graph is provably efficient for decentralized deep training B Ying, K Yuan, Y Chen, H Hu, P Pan, W Yin Advances in Neural Information Processing Systems 34, 13975-13987, 2021 | 63 | 2021 |
| Bluefog: Make decentralized algorithms practical for optimization and deep learning B Ying, K Yuan, H Hu, Y Chen, W Yin arXiv preprint arXiv:2111.04287, 2021 | 22 | 2021 |
| Enabling high-dimensional Bayesian optimization for efficient failure detection of analog and mixed-signal circuits H Hu, P Li, JZ Huang Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 20 | 2019 |
| Parallelizable Bayesian optimization for analog and mixed-signal rare failure detection with high coverage H Hu, P Li, JZ Huang 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-8, 2018 | 16 | 2018 |
| Topological approach to automatic symbolic macromodel generation for analog integrated circuits G Shi, H Hu, S Deng ACM Transactions on Design Automation of Electronic Systems (TODAES) 22 (3 …, 2017 | 16 | 2017 |
| Advanced outlier detection using unsupervised learning for screening potential customer returns H Hu, N Nguyen, C He, P Li 2020 IEEE International Test Conference (ITC), 1-10, 2020 | 13 | 2020 |
| Topological symbolic simplification for analog design H Hu, G Shi, A Tai, F Lee 2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2644-2647, 2015 | 10 | 2015 |
| Semi-supervised wafer map pattern recognition using domain-specific data augmentation and contrastive learning H Hu, C He, P Li 2021 IEEE International Test Conference (ITC), 113-122, 2021 | 9 | 2021 |
| HFMV: Hybridizing formal methods and machine learning for verification of analog and mixed-signal circuits H Hu, Q Zheng, Y Wang, P Li Proceedings of the 55th Annual Design Automation Conference, 1-6, 2018 | 9 | 2018 |
| Applications for machine learning in semiconductor manufacturing and test C He, H Hu, P Li 2021 5th IEEE Electron Devices Technology & Manufacturing Conference (EDTM), 1-3, 2021 | 8 | 2021 |
| Prioritized reinforcement learning for analog circuit optimization with design knowledge NSK Somayaji, H Hu, P Li 2021 58th ACM/IEEE Design Automation Conference (DAC), 1231-1236, 2021 | 7 | 2021 |
| Contrastive learning with consistent representations Z Wang, Y Wang, H Hu, P Li arXiv preprint arXiv:2302.01541, 2023 | 5 | 2023 |
| Global Adversarial Attacks for Assessing Deep Learning Robustness H Hu, M Shah, JZ Huang, P Li arXiv preprint arXiv:1906.07920, 2019 | 2 | 2019 |
| Reversible Gating Architecture for Rare Failure Detection of Analog and Mixed-Signal Circuits MS Shim, H Hu, P Li 2021 58th ACM/IEEE Design Automation Conference (DAC), 901-906, 2021 | 1 | 2021 |
| SPICE Model of Polyswitch Device H Hu, G Shi, Q Wang, T Dai, H Xia | 1 | |
| Recognizing Wafer Map Patterns Using Semi-Supervised Contrastive Learning with Optimized Latent Representation Learning and Data Augmentation Z Wang, H Hu, C He, P Li 2023 IEEE International Test Conference (ITC), 141-150, 2023 | | 2023 |
| Identifying Covid-19 Chest X-Rays by Image-Based Deep Learning A J. He, H Hu Proceedings of the 2022 7th International Conference on Machine Learning …, 2022 | | 2022 |
| Communicate Then Adapt: An Effective Decentralized Adaptive Method for Deep Training B Ying, K Yuan, Y Chen, H Hu, Y Zhang, P Pan, W Yin | | 2021 |
| Machine Learning Techniques for Rare Failure Detection in Analog and Mixed-Signal Verification and Test H Hu University of California, Santa Barbara, 2021 | | 2021 |
| Incremental symbolic construction for topological modeling of analog circuits H Hu, G Shi, Y Zhu 2013 IEEE 10th International Conference on ASIC, 1-4, 2013 | | 2013 |
Yan ZhuPhD Candidate in Computer Science, University of California, RiversideDirección de correo verificada de ucr.edu
