Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, MA, USA;
Department of Mathematical Sciences, Department of Computer Science and Data Science Program, Worcester Polytechnic Institute, MA, USA;
Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, MA, USA;
School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, USA;
School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, USA;
Space Communications and Navigation, NASA John H. Glenn Research Center, Cleveland, OH, USA;
Space Communications and Navigation, NASA John H. Glenn Research Center, Cleveland, OH, USA;
Artificial neural networks; Learning (artificial intelligence); Space communications; NASA; Resource management; Prediction algorithms;
机译:认知协作网络中的新型深度增强基于学习的延迟约束缓冲缓冲中继选择
机译:基于深度加强学习的资源分配策略,用于能源收集动力的认知机器到机网络
机译:基于深度加强学习的智能反射表面,用于安全无线通信
机译:基于多目标强化学习的认知空间通信深神经网络
机译:基于神经网络学习的大数据分析学习的分类器设计
机译:深度神经网络和深增强学习在无线通信中的应用
机译:认知异构网络中基于深度加强学习的调制和编码方案选择
机译:基于多目标强化学习的认知空间通信深度神经网络。