Streaming feature selection using alpha-investing
暂无分享,去创建一个
Jing Zhou | Dean P. Foster | Lyle H. Ungar | Robert A. Stine | Dean Phillips Foster | R. Stine | L. Ungar | Jing Zhou
[1] R. F.,et al. Mathematical Statistics , 1944, Nature.
[2] H. Akaike,et al. Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .
[3] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[4] A. Shiryaev,et al. Limit Theorems for Stochastic Processes , 1987 .
[5] I. Johnstone,et al. Ideal spatial adaptation by wavelet shrinkage , 1994 .
[6] Dean P. Foster,et al. The risk inflation criterion for multiple regression , 1994 .
[7] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[8] Dean Phillips Foster,et al. Calibration and Empirical Bayes Variable Selection , 1997 .
[9] Jorma Rissanen,et al. Hypothesis Selection and Testing by the MDL Principle , 1999, Comput. J..
[10] E. George. The Variable Selection Problem , 2000 .
[11] Dean P. Foster,et al. Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy , 2001 .
[12] Luc De Raedt,et al. Multirelational data mining 2003: workshop report , 2003, SKDD.
[13] Lyle H. Ungar,et al. Structural Logistic Regression for Link Analysis , 2003 .
[14] Lyle H. Ungar,et al. Cluster-based concept invention for statistical relational learning , 2004, KDD.
[15] R. Stine. Model Selection Using Information Theory and the MDL Principle , 2004 .
[16] I. Johnstone,et al. Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences , 2004, math/0410088.
[17] I. Johnstone,et al. Adapting to unknown sparsity by controlling the false discovery rate , 2005, math/0505374.
[18] Jing Zhou,et al. Streaming Feature Selection using IIC , 2005, AISTATS.