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Domain adaptive transfer learning with specialist models J Ngiam, D Peng, V Vasudevan, S Kornblith, QV Le, R Pang arXiv preprint arXiv:1811.07056, 2018 | 139 | 2018 |
Evolving reinforcement learning algorithms JD Co-Reyes, Y Miao, D Peng, E Real, S Levine, QV Le, H Lee, A Faust arXiv preprint arXiv:2101.03958, 2021 | 95 | 2021 |
AutoHAS: Efficient hyperparameter and architecture search X Dong, M Tan, AW Yu, D Peng, B Gabrys, QV Le arXiv preprint arXiv:2006.03656, 2020 | 46 | 2020 |
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Towards nngp-guided neural architecture search DS Park, J Lee, D Peng, Y Cao, J Sohl-Dickstein arXiv preprint arXiv:2011.06006, 2020 | 33 | 2020 |
Rethinking co-design of neural architectures and hardware accelerators Y Zhou, X Dong, B Akin, M Tan, D Peng, T Meng, A Yazdanbakhsh, ... arXiv preprint arXiv:2102.08619, 2021 | 32 | 2021 |
Long-form factuality in large language models J Wei, C Yang, X Song, Y Lu, N Hu, D Tran, D Peng, R Liu, D Huang, ... arXiv preprint arXiv:2403.18802, 2024 | 31 | 2024 |
Autohas: Differentiable hyper-parameter and architecture search X Dong, M Tan, AW Yu, D Peng, B Gabrys, QV Le arXiv preprint arXiv:2006.03656 4 (5), 2020 | 28 | 2020 |
Higher layers need more lora experts C Gao, K Chen, J Rao, B Sun, R Liu, D Peng, Y Zhang, X Guo, J Yang, ... arXiv preprint arXiv:2402.08562, 2024 | 25 | 2024 |
Brainformers: Trading simplicity for efficiency Y Zhou, N Du, Y Huang, D Peng, C Lan, D Huang, S Shakeri, D So, ... International Conference on Machine Learning, 42531-42542, 2023 | 21 | 2023 |
Towards the co-design of neural networks and accelerators Y Zhou, X Dong, T Meng, M Tan, B Akin, D Peng, A Yazdanbakhsh, ... Proceedings of Machine Learning and Systems 4, 141-152, 2022 | 18 | 2022 |
Best practices and lessons learned on synthetic data for language models R Liu, J Wei, F Liu, C Si, Y Zhang, J Rao, S Zheng, D Peng, D Yang, ... arXiv e-prints, arXiv: 2404.07503, 2024 | 10 | 2024 |
ES-ENAS: combining evolution strategies with neural architecture search at no extra cost for reinforcement learning X Song, K Choromanski, J Parker-Holder, Y Tang, D Peng, D Jain, W Gao, ... CoRR, abs/2101.07415, 2021 | 9 | 2021 |
RL-DARTS: differentiable architecture search for reinforcement learning Y Miao, X Song, D Peng, S Yue, JD Co-Reyes, E Brevdo, A Faust | 9 | 2021 |
Training machine learning models using adaptive transfer learning V Vasudevan, R Pang, QV Le, D Peng, J Ngiam, S Kornblith US Patent App. 16/586,675, 2020 | 9 | 2020 |
Omnipred: Language models as universal regressors X Song, O Li, C Lee, B Yang, D Peng, S Perel, Y Chen arXiv preprint arXiv:2402.14547, 2024 | 6 | 2024 |
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Differentiable architecture search for reinforcement learning Y Miao, X Song, JD Co-Reyes, D Peng, S Yue, E Brevdo, A Faust International Conference on Automated Machine Learning, 20/1-17, 2022 | 5 | 2022 |