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Laixi Shi
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2020 – today
- 2024
- [j3]Laixi Shi, Yuejie Chi:
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity. J. Mach. Learn. Res. 25: 200:1-200:91 (2024) - [c15]Laixi Shi, Eric Mazumdar, Yuejie Chi, Adam Wierman:
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty. ICML 2024 - [c14]Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi:
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices. ICML 2024 - [i18]Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi:
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices. CoRR abs/2402.05876 (2024) - [i17]He Wang, Laixi Shi, Yuejie Chi:
Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes. CoRR abs/2403.12946 (2024) - [i16]Laixi Shi, Eric Mazumdar, Yuejie Chi, Adam Wierman:
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty. CoRR abs/2404.18909 (2024) - [i15]Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas J. Spanos, Adam Wierman, Ming Jin:
Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation. CoRR abs/2405.20860 (2024) - [i14]Eric Mazumdar, Kishan Panaganti, Laixi Shi:
Tractable Equilibrium Computation in Markov Games through Risk Aversion. CoRR abs/2406.14156 (2024) - [i13]Zhengfei Zhang, Kishan Panaganti, Laixi Shi, Yanan Sui, Adam Wierman, Yisong Yue:
Distributionally Robust Constrained Reinforcement Learning under Strong Duality. CoRR abs/2406.15788 (2024) - [i12]Haohong Lin, Wenhao Ding, Jian Chen, Laixi Shi, Jiacheng Zhu, Bo Li, Ding Zhao:
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning. CoRR abs/2407.10967 (2024) - [i11]Laixi Shi, Jingchu Gai, Eric Mazumdar, Yuejie Chi, Adam Wierman:
Can We Break the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning? CoRR abs/2409.20067 (2024) - 2023
- [c13]Wenhao Ding, Laixi Shi, Yuejie Chi, Ding Zhao:
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation. NeurIPS 2023 - [c12]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi:
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. NeurIPS 2023 - [c11]Laixi Shi
, Robert Dadashi, Yuejie Chi
Offline Reinforcement Learning with On-Policy Q-Function Regularization. ECML/PKDD (4) 2023: 455-471 - [c10]Yiqi Wang, Mengdi Xu, Laixi Shi, Yuejie Chi:
A trajectory is worth three sentences: multimodal transformer for offline reinforcement learning. UAI 2023: 2226-2236 - [i10]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi:
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. CoRR abs/2305.16589 (2023) - [i9]Wenhao Ding, Laixi Shi, Yuejie Chi, Ding Zhao:
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation. CoRR abs/2307.07907 (2023) - [i8]Laixi Shi, Robert Dadashi, Yuejie Chi, Pablo Samuel Castro, Matthieu Geist:
Offline Reinforcement Learning with On-Policy Q-Function Regularization. CoRR abs/2307.13824 (2023) - 2022
- [c9]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity. ICML 2022: 19967-20025 - [c8]Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao:
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. NeurIPS 2022 - [i7]Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi:
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity. CoRR abs/2202.13890 (2022) - [i6]Gen Li, Laixi Shi, Yuxin Chen, Yuejie Chi, Yuting Wei:
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning. CoRR abs/2204.05275 (2022) - [i5]Laixi Shi, Yuejie Chi
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity. CoRR abs/2208.05767 (2022) - [i4]Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. CoRR abs/2210.10195 (2022) - 2021
- [j2]Laixi Shi
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently. IEEE Trans. Inf. Theory 67(7): 4784-4811 (2021) - [c7]Laixi Shi, Dehong Liu, Masaki Umeda, Norihiko Hana:
Fusion-Based Digital Image Correlation Framework for Strain Measurement. ICASSP 2021: 1400-1404 - [c6]Laixi Shi, Dehong Liu, Jay Thornton:
Robust Camera Pose Estimation For Image Stitching. ICIP 2021: 2838-2842 - [c5]Gen Li, Laixi Shi, Yuxin Chen, Yuantao Gu, Yuejie Chi:
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning. NeurIPS 2021: 17762-17776 - [i3]Gen Li, Laixi Shi, Yuxin Chen, Yuantao Gu, Yuejie Chi:
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning. CoRR abs/2110.04645 (2021) - 2020
- [c4]Laixi Shi, Yuejie Chi
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently. ICASSP 2020: 5730-5734 - [c3]Laixi Shi, Yue Zhang, Shijia Pan, Yuejie Chi
Data Quality-Informed Multiple Occupant Localization using Floor Vibration Sensing. HotMobile 2020: 98 - [c2]Yue Zhang
Using Mobile Sensing to Enable the Signal Quality Assessment for Infrastructure Sensing Systems. HotMobile 2020: 102
2010 – 2019
- 2019
- [c1]Laixi Shi, Mostafa Mirshekari, Jonathon Fagert, Yuejie Chi
Device-free Multiple People Localization through Floor Vibration. DFHS@BuildSys 2019: 57-61 - [i2]Laixi Shi, Yuejie Chi:
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently. CoRR abs/1911.11167 (2019) - 2018
- [j1]Yu Sang
Micro Hand Gesture Recognition System Using Ultrasonic Active Sensing. IEEE Access 6: 49339-49347 (2018) - 2017
- [i1]Yu Sang, Laixi Shi, Yimin Liu:
Micro Hand Gesture Recognition System Using Ultrasonic Active Sensing. CoRR abs/1712.00216 (2017)
Coauthor Index
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last updated on 2024-10-21 20:29 CEST by the dblp team
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