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Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
Submodular meets Spectral Greedy Algorithms for Subset Selection Sparse Approximation Dictionary Selection
2011/3/23
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can be viewed in the cont...
Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
Greedy Algorithms Subset Selection Dictionary Selection
2011/3/22
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can be viewed in the cont...
Best subset selection，persistence in high-dimensional statistical learning and optimization under L1 constraint
Variable selection persistence
2010/4/26
Let (Y,X1, . . . ,Xm) be a random vector. It is desired to predict Y
based on (X1, . . . ,Xm). Examples of prediction methods are regression,
classification using logistic regression or separating h...