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Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation
Juntao Dai, Yaodong Yang, Qian Zheng +1
A key aspect of Safe Reinforcement Learning (Safe RL) involves estimating the constraint condition for the next policy, which is crucial for guiding the optimization of safe policy…
Copiloting Diagnosis of Autism in Real Clinical Scenarios via LLMs
Yi Jiang, Qingyang Shen, Shuzhong Lai +5
Autism spectrum disorder(ASD) is a pervasive developmental disorder that significantly impacts the daily functioning and social participation of individuals. Despite the abundance…
Spiking GS: Towards High-Accuracy and Low-Cost Surface Reconstruction via Spiking Neuron-based Gaussian Splatting
Weixing Zhang, Zongrui Li, De Ma +4
3D Gaussian Splatting is capable of reconstructing 3D scenes in minutes. Despite recent advances in improving surface reconstruction accuracy, the reconstructed results still exhib…
Off-OAB: Off-Policy Policy Gradient Method with Optimal Action-Dependent Baseline
Wenjia Meng, Qian Zheng, Long Yang +2
Policy-based methods have achieved remarkable success in solving challenging reinforcement learning problems. Among these methods, off-policy policy gradient methods are particular…
Spin-UP: Spin Light for Natural Light Uncalibrated Photometric Stereo
Zongrui Li, Zhan Lu, Haojie Yan +4
Natural Light Uncalibrated Photometric Stereo (NaUPS) relieves the strict environment and light assumptions in classical Uncalibrated Photometric Stereo (UPS) methods. However, due…