机译:多重分类问题的联合协变量选择和联合子空间选择
Department of Statistics, University of California at Berkeley, 367 Evans Hall, Berkeley, CA 94720-3860, USA;
rnDepartment of Computer and Information Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104-6389, USA;
rnDepartment of Statistics and Department of Electrical Engineering and Computer Science, University of California at Berkeley, 367 Evans Hall, Berkeley, CA 94720-3860, USA;
variable selection; subspace selection; lasso; group lasso; regularization path; supervised dimensionality reduction; multitask learning; block norm; trace norm; random projections;
机译:将联合特征选择集成到子空间学习中:2DPCA用于异常值强大的特征选择
机译:基于统计和瞬时选择标准的空间复用系统联合天线子集选择
机译:具有缺失的协变量参数估计,联合建模框架内的模型选择和预测的逻辑回归
机译:通过联合无监督功能选择子空间聚类
机译:高维回归的联合和选择后的信心集
机译:多效选择和稳定选择对突变选择平衡维持定量遗传变异的联合影响。
机译:多重分类问题的联合协变量选择和联合子空间选择
机译:建立联合服务分类研究路线图:选择和分类中的方法问题