dpc-screening github.io
DPC Screening Methods for Sparse Models via Dual Projection onto Convex Set
DPC Screening Methods for Sparse Models via Dual Projection onto Convex Set. This package implements the highly effective screening rulesdeveloped under the DPC framework for many popular sparse learning models, like Lasso, non-negative Lasso, group Lasso, sparse-group Lasso etc. Highly effective in reducing the data size by discarding the irrelevant variables. Highly effective in speeding up any. Existing algorithms for solving the sparse learning models. DPC package 2.1.1.
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Jieping Ye, Ph.D.
Department of Computational Medicine and Bioinformatics. Department of Electrical Engineering and Computer Science. University of Michigan, Ann Arbor. Ann Arbor, MI 48109-2218.
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DPC Screening Methods for Sparse Models via Dual Projection onto Convex SetDESCRIPTION
DPC Screening Methods for Sparse Models via Dual Projection onto Convex Set. This package implements the highly effective screening rulesdeveloped under the DPC framework for many popular sparse learning models, like Lasso, non-negative Lasso, group Lasso, sparse-group Lasso etc. Highly effective in reducing the data size by discarding the irrelevant variables. Highly effective in speeding up any. Existing algorithms for solving the sparse learning models. DPC package 2.1.1.PARSED CONTENT
The site had the following in the web page, "DPC Screening Methods for Sparse Models via Dual Projection onto Convex Set." I observed that the web site stated " This package implements the highly effective screening rulesdeveloped under the DPC framework for many popular sparse learning models, like Lasso, non-negative Lasso, group Lasso, sparse-group Lasso etc." They also stated " Highly effective in reducing the data size by discarding the irrelevant variables. Highly effective in speeding up any. Existing algorithms for solving the sparse learning models."SEE MORE WEB PAGES
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