| Regularized evolution for image classifier architecture search E Real, A Aggarwal, Y Huang, QV Le Proceedings of the aaai conference on artificial intelligence 33 (01), 4780-4789, 2019 | 2694 | 2019 |
| GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism Y Huang, Y Cheng, A Bapna, O Firat, MX Chen, D Chen, HJ Lee, J Ngiam, ... Advances in Neural Information Processing Systems 32, 103--112, 2019 | 1086 | 2019 |
| Predictive coding Y Huang, RPN Rao Wiley Interdisciplinary Reviews: Cognitive Science 2 (5), 580-593, 2011 | 585 | 2011 |
| Gshard: Scaling giant models with conditional computation and automatic sharding D Lepikhin, HJ Lee, Y Xu, D Chen, O Firat, Y Huang, M Krikun, N Shazeer, ... International Conference on Learning Representations (ICLR), 2020 | 404 | 2020 |
| Lamda: Language models for dialog applications R Thoppilan, D De Freitas, J Hall, N Shazeer, A Kulshreshtha, HT Cheng, ... arXiv preprint arXiv:2201.08239, 2022 | 364 | 2022 |
| Scaling instruction-finetuned language models HW Chung, L Hou, S Longpre, B Zoph, Y Tay, W Fedus, E Li, X Wang, ... arXiv preprint arXiv:2210.11416, 2022 | 228 | 2022 |
| Lingvo: a modular and scalable framework for sequence-to-sequence modeling J Shen, P Nguyen, Y Wu, Z Chen, MX Chen, Y Jia, A Kannan, T Sainath, ... arXiv preprint arXiv:1902.08295, 2019 | 171 | 2019 |
| Glam: Efficient scaling of language models with mixture-of-experts N Du, Y Huang, AM Dai, S Tong, D Lepikhin, Y Xu, M Krikun, Y Zhou, ... International Conference on Machine Learning, 5547-5569, 2022 | 123 | 2022 |
| Bigssl: Exploring the frontier of large-scale semi-supervised learning for automatic speech recognition Y Zhang, DS Park, W Han, J Qin, A Gulati, J Shor, A Jansen, Y Xu, ... IEEE Journal of Selected Topics in Signal Processing 16 (6), 1519-1532, 2022 | 78 | 2022 |
| Just pick a sign: Optimizing deep multitask models with gradient sign dropout Z Chen, J Ngiam, Y Huang, T Luong, H Kretzschmar, Y Chai, D Anguelov Advances in Neural Information Processing Systems 33, 2039-2050, 2020 | 75 | 2020 |
| Renelito Delos Santos R Thoppilan, D De Freitas, J Hall, N Shazeer, A Kulshreshtha, HT Cheng, ... | 57 | 2022 |
| GSPMD: general and scalable parallelization for ML computation graphs Y Xu, HJ Lee, D Chen, B Hechtman, Y Huang, R Joshi, M Krikun, ... arXiv preprint arXiv:2105.04663, 2021 | 57 | 2021 |
| Alpa: Automating Inter-and Intra-Operator Parallelism for Distributed Deep Learning L Zheng, Z Li, H Zhang, Y Zhuang, Z Chen, Y Huang, Y Wang, Y Xu, ... 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2022 | 52 | 2022 |
| Neurons as Monte Carlo samplers: Bayesian Inference and Learning in Spiking Networks Y Huang, RPN Rao Advances in neural information processing systems 27, 1943-1951, 2014 | 48 | 2014 |
| Reward optimization in the primate brain: A probabilistic model of decision making under uncertainty Y Huang, RPN Rao PloS one 8 (1), e53344, 2013 | 43 | 2013 |
| Designing effective sparse expert models B Zoph, I Bello, S Kumar, N Du, Y Huang, J Dean, N Shazeer, W Fedus arXiv preprint arXiv:2202.08906 2, 2022 | 39 | 2022 |
| Beyond distillation: Task-level mixture-of-experts for efficient inference S Kudugunta, Y Huang, A Bapna, M Krikun, D Lepikhin, MT Luong, O Firat arXiv preprint arXiv:2110.03742, 2021 | 34 | 2021 |
| How prior probability influences decision making: A unifying probabilistic model Y Huang, T Hanks, M Shadlen, AL Friesen, RP Rao Advances in neural information processing systems 25, 1268-1276, 2012 | 33 | 2012 |
| Mixture-of-experts with expert choice routing Y Zhou, T Lei, H Liu, N Du, Y Huang, V Zhao, AM Dai, QV Le, J Laudon Advances in Neural Information Processing Systems 35, 7103-7114, 2022 | 21 | 2022 |
| Building machine translation systems for the next thousand languages A Bapna, I Caswell, J Kreutzer, O Firat, D van Esch, A Siddhant, M Niu, ... arXiv preprint arXiv:2205.03983, 2022 | 21 | 2022 |
Quoc V. LeResearch Scientist, Google BrainVerified email at stanford.edu
