Publications (7)
Navigating Open Set Scenarios for Skeleton-based Action Recognition
Kunyu Peng, Cheng Yin, Junwei Zheng +7
In real-world scenarios, human actions often fall outside the distribution of training data, making it crucial for models to recognize known actions and reject unknown ones. Howeve…
A Method to Improve the Performance of Reinforcement Learning Based on the Y Operator for a Class of Stochastic Differential Equation-Based Child-Mother Systems
Cheng Yin, Yi Chen
This paper introduces a novel operator, termed the Y operator, to elevate control performance in Actor-Critic(AC) based reinforcement learning for systems governed by stochastic di…
Does Optimal Control Always Benefit from Better Prediction? An Analysis Framework for Predictive Optimal Control
Xiangrui Zeng, Cheng Yin, Zhouping Yin
The ``prediction + optimal control'' scheme has shown good performance in many applications of automotive, traffic, robot, and building control. In practice, the prediction results…
Deep Reinforcement Learning for Intelligent Reflecting Surface-assisted D2D Communications
Khoi Khac Nguyen, Antonino Masaracchia, Cheng Yin +3
In this paper, we propose a deep reinforcement learning (DRL) approach for solving the optimisation problem of the network's sum-rate in device-to-device (D2D) communications suppo…
Pseudopotential MRT lattice Boltzmann model for cavitation bubble collapse with high density ratio
Ming-Lei Shan, Chang-Ping Zhu, Cheng Yao +2
The dynamics of the cavitation bubble collapse is a fundamental issue for the bubble collapse application and prevention. In present work, the modified forcing scheme for the pseud…
DeepThinkVLA: Enhancing Reasoning Capability of Vision-Language-Action Models
Cheng Yin, Yankai Lin, Wang Xu +4
Does Chain-of-Thought (CoT) reasoning genuinely improve Vision Language Action (VLA) models, or does it merely add overhead? Existing CoT-VLA systems report limited and inconsisten…