| SBEED: Convergent reinforcement learning with nonlinear function approximation B Dai, A Shaw, L Li, L Xiao, N He, Z Liu, J Chen, L Song International conference on machine learning, 1125-1134, 2018 | 298 | 2018 |
| SqueezeBERT: What can computer vision teach NLP about efficient neural networks? FN Iandola, AE Shaw, R Krishna, KW Keutzer arXiv preprint arXiv:2006.11316, 2020 | 119 | 2020 |
| Squeezenas: Fast neural architecture search for faster semantic segmentation A Shaw, D Hunter, F Landola, S Sidhu Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 83 | 2019 |
| Squeezeformer: An efficient transformer for automatic speech recognition S Kim, A Gholami, A Shaw, N Lee, K Mangalam, J Malik, MW Mahoney, ... Advances in Neural Information Processing Systems 35, 9361-9373, 2022 | 78 | 2022 |
| Meta architecture search A Shaw, W Wei, W Liu, L Song, B Dai Advances in Neural Information Processing Systems 32, 2019 | 43 | 2019 |
| Boosting the actor with dual critic B Dai, A Shaw, N He, L Li, L Song arXiv preprint arXiv:1712.10282, 2017 | 43 | 2017 |
| SqueezeBERT: What can computer vision teach NLP about efficient neural networks? arXiv 2020 FN Iandola, AE Shaw, R Krishna, KW Keutzer arXiv preprint arXiv:2006.11316, 2006 | 8 | 2006 |
| Learning disentangled prompts for compositional image synthesis K Sohn, A Shaw, Y Hao, H Zhang, L Polania, H Chang, L Jiang, I Essa arXiv preprint arXiv:2306.00763, 2023 | 3 | 2023 |
