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机译:避免基于最优均值ℓ2,1-范数最大化的鲁棒PCA进行重构
SPKLSTN Lab, Department of Computer Science, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, China minnluo@xjtu.edu.cn;
Center for OPTical Imagery Analysis and Learning, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, China feipingnie@gmail.com;
Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, 2007 NSW, Australia cxj273@gmail.com;
Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, 2007 NSW, Australia yee.i.yang@gmail.com;
School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, U.S.A. alex@cs.cmv.edu;
SPKLSTN Lab, Department of Computer Science, Xi’an Jiatong University, Xi’an, Shaanxi 710049, China qhzheng@mail.xjtu.edu.cn;
机译:避免最佳平均值L(2,1) - 基于最大化的鲁棒PCA进行重建
机译:基于l(2,1)-范数正则化最小二乘和贝叶斯最优重构的分布式压缩感知的典型重构性能:噪声的影响
机译:基于l(2,1)-范数最小化和贝叶斯最优重构的分布式压缩感知的典型重构极限
机译:具有非贪婪L_1-Norm最大化的最佳平均稳健PCA / 2DPCA
机译:通过稀疏规则化强制PCA和强大的线性回归
机译:基于鲁棒PCA的室内定位指纹数据库重建
机译:通过l2,1-范数正则化进行鲁棒分类的最佳特征选择