| Pessimistic Q-learning for offline reinforcement learning: Towards optimal sample complexity L Shi, G Li, Y Wei, Y Chen, Y Chi International Conference on Machine Learning (ICML), 2022, 2022 | 110 | 2022 |
| Settling the sample complexity of model-based offline reinforcement learning G Li, L Shi, Y Chen, Y Chi, Y Wei The Annals of Statistics 52 (1), 233-260, 2024 | 96 | 2024 |
| Micro hand gesture recognition system using ultrasonic active sensing Y Sang, L Shi, Y Liu IEEE Access 6, 49339-49347, 2018 | 90 | 2018 |
| Distributionally robust model-based offline reinforcement learning with near-optimal sample complexity L Shi, Y Chi Journal of Machine Learning Research 25 (200), 1-91, 2024 | 64 | 2024 |
| Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning G Li, L Shi, Y Chen, Y Chi Information and Inference: A Journal of the IMA; Short version as NeurIPS …, 2023 | 63 | 2023 |
| The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model L Shi, G Li, Y Wei, Y Chen, M Geist, Y Chi Conference on Neural Information Processing Systems (NeurIPS), 2023, 2023 | 39 | 2023 |
| Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation P Huang, M Xu, J Zhu, L Shi, F Fang, D Zhao Conference on Neural Information Processing Systems (NeurIPS), 2022, 2022 | 31 | 2022 |
| Manifold gradient descent solves multi-channel sparse blind deconvolution provably and efficiently L Shi, Y Chi IEEE Transactions on Information Theory 67 (7), 4784-4811, 2021 | 31 | 2021 |
| Device-free multiple people localization through floor vibration L Shi, M Mirshekari, J Fagert, Y Chi, HY Noh, P Zhang, S Pan Proceedings of the 1st ACM International Workshop on Device-Free Human …, 2019 | 30 | 2019 |
| Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation W Ding*, L Shi*, Y Chi, D Zhao Conference on Neural Information Processing Systems (NeurIPS), 2023, 2023 | 24* | 2023 |
| Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty L Shi, E Mazumdar, Y Chi, A Wierman International Conference on Machine Learning (ICML), 2024, 2024 | 10 | 2024 |
| Sample complexity of offline distributionally robust linear markov decision processes H Wang, L Shi, Y Chi arXiv preprint arXiv:2403.12946, 2024 | 10 | 2024 |
| A trajectory is worth three sentences: multimodal transformer for offline reinforcement learning Y Wang, M Xu, L Shi, Y Chi Uncertainty in Artificial Intelligence, 2226-2236, 2023 | 9 | 2023 |
| Federated offline reinforcement learning: Collaborative single-policy coverage suffices J Woo, L Shi, G Joshi, Y Chi arXiv preprint arXiv:2402.05876, 2024 | 7 | 2024 |
| Offline Reinforcement Learning with On-Policy Q-Function Regularization L Shi, R Dadashi, Y Chi, PS Castro, M Geist European Conference on Machine Learning (ECML), 2023, 2023 | 3 | 2023 |
| Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation S Gu*, L Shi*, Y Ding, A Knoll, C Spanos, A Wierman, M Jin Conference on Neural Information Processing Systems (NeurIPS), 2024, 2024 | 2 | 2024 |
| Zoom Out: Abstractions for Efficient Radar Algorithms on COTS architectures TM Low, Y Chi, J Hoe, S Kumar, A Prabhakara, L Shi, U Sridhar, ... 2022 IEEE International Symposium on Phased Array Systems & Technology (PAST …, 2022 | 2 | 2022 |
| Robust Camera Pose Estimation For Image Stitching L Shi, D Liu, J Thornton 2021 IEEE International Conference on Image Processing (ICIP), 2838-2842, 2021 | 2 | 2021 |
| Fusion-based digital image correlation framework for strain measurement L Shi, D Liu, M Umeda, N Hana ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 2 | 2021 |
| Tractable Equilibrium Computation in Markov Games through Risk Aversion E Mazumdar*, K Panaganti*, L Shi* arXiv preprint arXiv:2406.14156, 2024 | 1 | 2024 |
Yuejie ChiCarnegie Mellon Universitycmu.edu의 이메일 확인됨