机译:低秩分解满足内核学习:广义Nyström方法
Lenovo Group Limited, 100 Cyberport Road, Hong Kong;
Department of Computer and Information Sciences, Temple University, Philadelphia, PA, United States;
Department of Computer Science and Engineering, Texas A&M University, Texas, United States;
NEC Laboratories America, Princeton, United States;
SAS Institute Inc., Cary, NC, United States;
Institute of Softwares and Interactive Systems, Technical University of Vienna, Austria;
Institute for Infocomm Research, Singapore;
School of Computer Science and Software Engineering, East China Normal University, Shanghai, China;
School of Computer Science and Software Engineering, East China Normal University, Shanghai, China,College of Computing, Georgia Institute of Technology, Atlanta, GA, United States;
Kernel learning; Large-scale learning algorithms; Multiple kernel learning; Nyström low-rank decomposition;
机译:通过分层NYSTR的基于内核的语言学习有效和可扩展的内核 - M方法
机译:基于多个内核学习的多NYSTR?M方法大规模非平衡分类
机译:基于Nystr ?? m逼近语法矩阵的改进基于核的学习方法
机译:动态学习的增量Nyström低秩分解
机译:计算稀疏概括的逆和稀疏 - 逆/低秩分解
机译:基于多核学习大规模的多NYStröm方法用于大规模不平衡分类
机译:内核方法的预测性低秩分解