机译:使用贝叶斯网络学习特权信息
School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China,Key Lab of Computing and Communicating Software of Anhui Province, Hefei 230027, China;
School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China,Key Lab of Computing and Communicating Software of Anhui Province, Hefei 230027, China;
School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China,Key Lab of Computing and Communicating Software of Anhui Province, Hefei 230027, China;
School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China,Key Lab of Computing and Communicating Software of Anhui Province, Hefei 230027, China;
School of Mathematical Sciences, University of Science and Technology of China, Hefei 230027, China;
Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy NY 12180-3590, USA;
Bayesian network; privileged information; classification; maximum likelihood estimation;
机译:贝叶斯网络:参数化的非频率方法,以及更准确的结构复杂性度量。贝叶斯网络学习
机译:模糊贝叶斯网络-混合贝叶斯网络表示,推理和学习的一般形式
机译:基于贝叶斯网络和学习自动机的认知无线传感器网络推理与学习新模型
机译:MIML-FCN +:通过具有特权信息的完全卷积网络进行多实例多标签学习
机译:一种基于稀疏邻居贝叶斯网络学习的微阵列实验推断遗传调控网络的新方法。
机译:贝叶斯学习的Python环境:从知识和数据中推断贝叶斯网络的结构
机译:mImL-FCN +:通过完全卷积的多实例多标签学习 具有特权信息的网络