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2020 – today
- 2024
[j1]Yiwen Dong
, Sung Eun Kim, Kornel Schadl, Peide Huang, Wenhao Ding, Jessica Rose, Hae Young Noh:
In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning. IEEE J. Biomed. Health Informatics 28(12): 7054-7067 (2024)- [c12]Gaocai Fu, Yu Jiang, Jun Xiao, Peide Huang, Xu Luo, Minhui Ni, Xianjv Liu:
Construction of Virtual Simulation Teaching Platform for Risk Experimental Projects in VR Environment. ICSIM 2024: 92-97 - [c11]Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao:
Gradient shaping for multi-constraint safe reinforcement learning. L4DC 2024: 25-39 - [i13]Peide Huang, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao:
CaDRE: Controllable and Diverse Generation of Safety-Critical Driving Scenarios using Real-World Trajectories. CoRR abs/2403.13208 (2024) - [i12]Xilun Zhang, Shiqi Liu, Peide Huang, William Jongwon Han, Yiqi Lyu, Mengdi Xu, Ding Zhao:
Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications. CoRR abs/2410.20357 (2024) - [i11]Peide Huang, Yuhan Hu, Nataliya Nechyporenko, Daehwa Kim, Walter Talbott, Jian Zhang:
EMOTION: Expressive Motion Sequence Generation for Humanoid Robots with In-Context Learning. CoRR abs/2410.23234 (2024) - 2023
- [c10]Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao:
Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables. AISTATS 2023: 2677-2703 - [c9]Shiqi Liu, Mengdi Xu, Peide Huang, Xilun Zhang, Yongkang Liu, Kentaro Oguchi, Ding Zhao:
Continual Vision-based Reinforcement Learning with Group Symmetries. CoRL 2023: 222-240 - [c8]Peide Huang, Xilun Zhang, Ziang Cao, Shiqi Liu, Mengdi Xu, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao:
What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery. CoRL 2023: 734-760 - [c7]Jielin Qiu, Jiacheng Zhu, Mengdi Xu, Peide Huang, Michael A. Rosenberg, Douglas Weber, Emerson Liu, Ding Zhao:
Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation. ICASSP 2023: 1-5 - [c6]Yiwen Dong, Yuyan Wu, Jesse R. Codling, Jatin Aggarwal, Peide Huang, Wenhao Ding, Hugo Latapie, Pei Zhang, Hae Young Noh:
GameVibes: Vibration-based Crowd Monitoring for Sports Games through Audience-Game-Facility Association Modeling. BuildSys 2023: 177-188 - [c5]Yiwen Dong, Peide Huang, Hae Young Noh:
Characterizing Crowd Preferences on Stadium Facilities through Dynamic Inverse Reinforcement Learning. BuildSys 2023: 305-306 - [i10]Jielin Qiu, Peide Huang, Makiya Nakashima, Jaehyun Lee, Jiacheng Zhu, W. H. Wilson Tang, Pohao Chen, Christopher Nguyen, Byung-Hak Kim, Debbie Kwon, Douglas Weber, Ding Zhao, David Chen:
Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging. CoRR abs/2304.07675 (2023) - [i9]Peide Huang, Xilun Zhang, Ziang Cao, Shiqi Liu, Mengdi Xu, Wenhao Ding, Jonathan Francis, Bingqing Chen, Ding Zhao:
What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery. CoRR abs/2306.15864 (2023) - [i8]Mengdi Xu, Peide Huang, Wenhao Yu, Shiqi Liu, Xilun Zhang, Yaru Niu, Tingnan Zhang, Fei Xia, Jie Tan, Ding Zhao:
Creative Robot Tool Use with Large Language Models. CoRR abs/2310.13065 (2023) - [i7]Yihang Yao, Zuxin Liu, Zhepeng Cen, Peide Huang, Tingnan Zhang, Wenhao Yu, Ding Zhao:
Gradient Shaping for Multi-Constraint Safe Reinforcement Learning. CoRR abs/2312.15127 (2023) - 2022
- [c4]Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao:
Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training. IJCAI 2022: 3099-3106 - [c3]Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao:
Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling. IROS 2022: 12919-12926 - [c2]Diana Gómez, Haohong Lin, Peide Huang, Corey Harper, Ding Zhao:
Coalitional Fairness of Autonomous Vehicles at a T-Intersection. ITSC 2022: 2536-2541 - [c1]Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao:
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. NeurIPS 2022 - [i6]Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao:
Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training. CoRR abs/2202.09514 (2022) - [i5]Mengdi Xu, Zuxin Liu, Peide Huang, Wenhao Ding, Zhepeng Cen, Bo Li, Ding Zhao:
Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. CoRR abs/2209.08025 (2022) - [i4]Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao:
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. CoRR abs/2210.10195 (2022) - [i3]Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao:
Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables. CoRR abs/2210.12262 (2022) - [i2]Shiqi Liu, Mengdi Xu, Peide Huang, Yongkang Liu, Kentaro Oguchi, Ding Zhao:
Continual Reinforcement Learning with Group Symmetries. CoRR abs/2210.12301 (2022) - 2021
- [i1]Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao:
Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling. CoRR abs/2106.10566 (2021)
Coauthor Index
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