Hanbin Hu
Hanbin Hu
Software Engineer at Google LLC
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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
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
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
Enabling high-dimensional bayesian optimization for efficient failure detection of analog and mixed-signal circuits
H Hu, P Li, JZ Huang
2019 56th ACM/IEEE Design Automation Conference (DAC), 1-6, 2019
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
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
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
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
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
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
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
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
Global Adversarial Attacks for Assessing Deep Learning Robustness
H Hu, M Shah, JZ Huang, P Li
arXiv preprint arXiv:1906.07920, 2019
Identifying Covid-19 Chest X-Rays by Image-Based Deep Learning
A J. He, H Hu
2022 7th International Conference on Machine Learning Technologies (ICMLT …, 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
Machine Learning Techniques for Rare Failure Detection in Analog and Mixed-Signal Verification and Test
H Hu
University of California, Santa Barbara, 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
A Symbolic Sensitivity Method for Mismatch Analysis and CMRR Improvement
S Deng, H Hu, G Shi
Assessment of Machine Learning Robustness for Analog and Mixed Signal Verification
H Hu, Y He, P Li
SPICE Model of Polyswitch Device
H Hu, G Shi, Q Wang, T Dai, H Xia
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