Micro Hand Gesture Recognition System Using Ultrasonic Active Sensing. - Yu Sang; Laixi Shi; Yimin Liu (IEEE Access, 2018)

Device-free Multiple People Localization through Floor Vibration. - Laixi Shi; Mostafa Mirshekari; Jonathon Fagert; Yuejie Chi; Hae Young Noh; Pei Zhang 001; Shijia Pan (DFHS@BuildSys, 2019)

Data Quality-Informed Multiple Occupant Localization using Floor Vibration Sensing. - Laixi Shi; Yue Zhang 044; Shijia Pan; Yuejie Chi (HotMobile, 2020)

Using Mobile Sensing to Enable the Signal Quality Assessment for Infrastructure Sensing Systems. - Yue Zhang 044; Susu Xu; Laixi Shi; Shijia Pan (HotMobile, 2020)

Fusion-Based Digital Image Correlation Framework for Strain Measurement. - Laixi Shi; Dehong Liu; Masaki Umeda; Norihiko Hana (ICASSP, 2021)

Robust Camera Pose Estimation For Image Stitching. - Laixi Shi; Dehong Liu; Jay Thornton (ICIP, 2021)

Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning. - Gen Li 005; Laixi Shi; Yuxin Chen 002; Yuantao Gu; Yuejie Chi (NeurIPS, 2021)

Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently. - Laixi Shi; Yuejie Chi (IEEE Trans. Inf. Theory, 2021)

Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity. - Laixi Shi; Gen Li 005; Yuting Wei 001; Yuxin Chen 002; Yuejie Chi (ICML, 2022)

Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. - Peide Huang; Mengdi Xu; Jiacheng Zhu; Laixi Shi; Fei Fang 001; Ding Zhao (NeurIPS, 2022)

Settling the Sample Complexity of Model-Based Offline Reinforcement Learning. - Gen Li 005; Laixi Shi; Yuxin Chen 002; Yuejie Chi; Yuting Wei 001 (CoRR, 2022)

Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation. - Wenhao Ding; Laixi Shi; Yuejie Chi; Ding Zhao (NeurIPS, 2023)

The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model. - Laixi Shi; Gen Li 005; Yuting Wei 001; Yuxin Chen 002; Matthieu Geist; Yuejie Chi (NeurIPS, 2023)

Offline Reinforcement Learning with On-Policy Q-Function Regularization. - Laixi Shi; Robert Dadashi; Yuejie Chi; Pablo Samuel Castro; Matthieu Geist (ECML/PKDD (4), 2023)

A trajectory is worth three sentences: multimodal transformer for offline reinforcement learning. - Yiqi Wang; Mengdi Xu; Laixi Shi; Yuejie Chi (UAI, 2023)

Provable Algorithms for Reinforcement Learning: Efficiency, Scalability, and Robustness - Laixi Shi (2023)

Scalable Dynamic Resource Allocation via Domain Randomized Reinforcement Learning. - Yiqi Wang; Laixi Shi; Martin Hyungwoo Lee; Jaroslaw Sydir; Zhu Zhou; Yuejie Chi; Bin Li 018 (GLOBECOM, 2024)

Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty. - Laixi Shi; Eric Mazumdar; Yuejie Chi; Adam Wierman (ICML, 2024)

Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices. - Jiin Woo; Laixi Shi; Gauri Joshi; Yuejie Chi (ICML, 2024)

Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms. - Pierre Clavier; Laixi Shi; Erwan Le Pennec; Eric Mazumdar; Adam Wierman; Matthieu Geist (NeurIPS, 2024)

Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation. - Shangding Gu; Laixi Shi; Yuhao Ding; Alois Knoll; Costas J. Spanos; Adam Wierman; Ming Jin 002 (NeurIPS, 2024)

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning. - Haohong Lin; Wenhao Ding; Jian Chen; Laixi Shi; Jiacheng Zhu; Bo Li; Ding Zhao (NeurIPS, 2024)

Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes. - He Wang 017; Laixi Shi; Yuejie Chi (RLJ, 2024)

Distributionally Robust Constrained Reinforcement Learning under Strong Duality. - Zhengfei Zhang; Kishan Panaganti; Laixi Shi; Yanan Sui; Adam Wierman; Yisong Yue (RLJ, 2024)

Tractable Equilibrium Computation in Markov Games through Risk Aversion. - Eric Mazumdar; Kishan Panaganti; Laixi Shi (CoRR, 2024)

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning. - Haohong Lin; Wenhao Ding; Jian Chen; Laixi Shi; Jiacheng Zhu; Bo Li 026; Ding Zhao (CoRR, 2024)

Can We Break the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning? - Laixi Shi; Jingchu Gai; Eric Mazumdar; Yuejie Chi; Adam Wierman (CoRR, 2024)

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization. - Chenbei Lu; Laixi Shi; Zaiwei Chen; Chenye Wu; Adam Wierman (CoRR, 2024)

Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity. - Laixi Shi; Yuejie Chi (J. Mach. Learn. Res., 2024)

Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data. - Chengrui Qu; Laixi Shi; Kishan Panaganti; Pengcheng You; Adam Wierman (AISTATS, 2025)

Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning. - Shangding Gu; Laixi Shi; Muning Wen; Ming Jin 002; Eric Mazumdar; Yuejie Chi; Adam Wierman; Costas J. Spanos (ICLR, 2025)

Tractable Multi-Agent Reinforcement Learning through Behavioral Economics. - Eric Mazumdar; Kishan Panaganti; Laixi Shi (ICLR, 2025)

KL-regularization Itself is Differentially Private in Bandits and RLHF. - Yizhou Zhang; Kishan Panaganti; Laixi Shi; Juba Ziani; Adam Wierman (CoRR, 2025)

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning. - Yiqing Liang; Jielin Qiu; Wenhao Ding; Zuxin Liu; James Tompkin 001; Mengdi Xu; Mengzhou Xia; Zhengzhong Tu; Laixi Shi; Jiacheng Zhu (CoRR, 2025)