| A survey of quantization methods for efficient neural network inference A Gholami, S Kim, Z Dong, Z Yao, MW Mahoney, K Keutzer Low-power computer vision, 291-326, 2022 | 1406 | 2022 |
| Q-bert: Hessian based ultra low precision quantization of bert S Shen, Z Dong, J Ye, L Ma, Z Yao, A Gholami, MW Mahoney, K Keutzer Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8815-8821, 2020 | 618 | 2020 |
| Hawq: Hessian aware quantization of neural networks with mixed-precision Z Dong, Z Yao, A Gholami, MW Mahoney, K Keutzer Proceedings of the IEEE/CVF international conference on computer vision, 293-302, 2019 | 592 | 2019 |
| Zeroq: A novel zero shot quantization framework Y Cai, Z Yao, Z Dong, A Gholami, MW Mahoney, K Keutzer Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 484 | 2020 |
| How much can clip benefit vision-and-language tasks? S Shen, LH Li, H Tan, M Bansal, A Rohrbach, KW Chang, Z Yao, ... arXiv preprint arXiv:2107.06383, 2021 | 461 | 2021 |
| Zeroquant: Efficient and affordable post-training quantization for large-scale transformers Z Yao, R Yazdani Aminabadi, M Zhang, X Wu, C Li, Y He Advances in Neural Information Processing Systems 35, 27168-27183, 2022 | 407 | 2022 |
| I-bert: Integer-only bert quantization S Kim, A Gholami, Z Yao, MW Mahoney, K Keutzer International conference on machine learning, 5506-5518, 2021 | 391 | 2021 |
| Pyhessian: Neural networks through the lens of the hessian Z Yao, A Gholami, K Keutzer, MW Mahoney 2020 IEEE international conference on big data (Big data), 581-590, 2020 | 335 | 2020 |
| Hawq-v2: Hessian aware trace-weighted quantization of neural networks Z Dong, Z Yao, D Arfeen, A Gholami, MW Mahoney, K Keutzer Advances in neural information processing systems 33, 18518-18529, 2020 | 311 | 2020 |
| Adahessian: An adaptive second order optimizer for machine learning Z Yao, A Gholami, S Shen, M Mustafa, K Keutzer, M Mahoney proceedings of the AAAI conference on artificial intelligence 35 (12), 10665 …, 2021 | 304 | 2021 |
| Hawq-v3: Dyadic neural network quantization Z Yao, Z Dong, Z Zheng, A Gholami, J Yu, E Tan, L Wang, Q Huang, ... International Conference on Machine Learning, 11875-11886, 2021 | 288 | 2021 |
| Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation ai scale S Rajbhandari, C Li, Z Yao, M Zhang, RY Aminabadi, AA Awan, J Rasley, ... International conference on machine learning, 18332-18346, 2022 | 257 | 2022 |
| Shallow neural networks for fluid flow reconstruction with limited sensors NB Erichson, L Mathelin, Z Yao, SL Brunton, MW Mahoney, JN Kutz Proceedings of the Royal Society A 476 (2238), 20200097, 2020 | 250 | 2020 |
| Hessian-based analysis of large batch training and robustness to adversaries Z Yao, A Gholami, Q Lei, K Keutzer, MW Mahoney Advances in Neural Information Processing Systems 31, 2018 | 183 | 2018 |
| ANODEV2: A coupled neural ODE framework T Zhang, Z Yao, A Gholami, JE Gonzalez, K Keutzer, MW Mahoney, ... Advances in Neural Information Processing Systems 32, 2019 | 110 | 2019 |
| Powernorm: Rethinking batch normalization in transformers S Shen, Z Yao, A Gholami, M Mahoney, K Keutzer International conference on machine learning, 8741-8751, 2020 | 100 | 2020 |
| Improving semi-supervised federated learning by reducing the gradient diversity of models Z Zhang, Y Yang, Z Yao, Y Yan, JE Gonzalez, K Ramchandran, ... 2021 IEEE International Conference on Big Data (Big Data), 1214-1225, 2021 | 96 | 2021 |
| AI and memory wall A Gholami, Z Yao, S Kim, C Hooper, MW Mahoney, K Keutzer IEEE Micro, 2024 | 90 | 2024 |
| Scaling vision-language models with sparse mixture of experts S Shen, Z Yao, C Li, T Darrell, K Keutzer, Y He arXiv preprint arXiv:2303.07226, 2023 | 89 | 2023 |
| On the computational inefficiency of large batch sizes for stochastic gradient descent N Golmant, N Vemuri, Z Yao, V Feinberg, A Gholami, K Rothauge, ... arXiv preprint arXiv:1811.12941, 2018 | 86 | 2018 |
Michael MahoneyProfessor of Statistics, UC Berkeleyยืนยันอีเมลแล้วที่ stat.berkeley.edu
