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Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation
Object detection and multiple object tracking (MOT) are essential components of self-driving systems. Accurate detection and …
Sanbao Su, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao
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Robust Multi-Agent Reinforcement Learning with State Uncertainty
In real-world multi-agent reinforcement learning (MARL) applications, agents may not have perfect state information (e.g., due to …
Sihong He, Songyang Han, Sanbao Su, Shuo Han, Shaofeng Zou, Fei Miao
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VECBEE A Versatile Efficiency-Accuracy Configurable Batch Error Estimation Method for Greedy Approximate Logic Synthesis
Approximate computing is an emerging strategy to improve the energy efficiency of many error-tolerant applications. To design …
Sanbao Su, Chang Meng, Fan Yang, Xiaolong Shen, Leibin Ni, Wei Wu, Zhihang Wu, Junfeng Zhao, Weikang Qian
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A Novel Heuristic Search Method for Two-Level Approximate Logic Synthesis
Recently, much attention has been paid to approximate computing, a novel design paradigm for error-tolerant applications. It can …
Sanbao Su, Chen Zou, Weijiang Kong, Jie Han, Weikang Qian
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