机译:基于希尔伯特-施密特独立性准则的两阶段模糊多核学习
School of Mathematics and Computer Science, Gannan Normal University, Ganzhou, China;
Centre for Artificial Intelligence, School of Software, Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, NSW, Australia;
Centre for Artificial Intelligence, School of Software, Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, NSW, Australia;
Kernel; Support vector machines; Optimization; Classification algorithms; Task analysis; Computational modeling; Data models;
机译:基于希尔伯特-施密特独立性准则的内核学习和优化
机译:稀疏Hilbert Schmidt独立准则和基于替代核的特征选择用于高光谱图像分类
机译:Hilbert-Schmidt独立性准则中的内核参数选择
机译:基于Hilbert-Schmidt独立性标准和居中内核目标对齐的规范相关分析
机译:通过Hilbert-Schmidt独立标准学习
机译:通过统计学习在内核Hilbert空间中进行高阶顺序模拟
机译:稀疏Hilbert Schmidt独立准则和基于替代核的特征选择用于高光谱图像分类