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Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling (ICML 2016)

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#Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling (ICML'16)

##Abstract

The problem of learning a sparse model is conceptually interpreted as the process of identifying active features/samples and then optimizing the model over them. Recently introduced safe screening allows us to identify a part of non-active features/samples. So far, safe screening has been individually studied either for feature screening or for sample screening. In this paper, we introduce a new approach for safely screening features and samples simultaneously by alternatively iterating feature and sample screening steps. A significant advantage of considering them simultaneously rather than individually is that they have a synergy effect in the sense that the results of the previous safe feature screening can be exploited for improving the next safe sample screening performances, and vice-versa. We first theoretically investigate the synergy effect, and then illustrate the practical advantage through intensive numerical experiments for problems with large numbers of features and samples.

##Result

##Enviromental Requirement

  • gcc version > 4.8.0
  • cmake version > 2.8.12

##About Source code for Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling. We wrote the code in C++ along with Eigen3.3-alpha1 library for some numerical computations.

##How to Compile

cd s3fs
cmake .
make

Usage

###We support LIBSVM data fortmat only ( LIBSVM datasets ).

###Elastic net + smoothed hinge loss (model selection task) with SPDC

  • non-screeing: ./test/elastic_smooth_module -s 14 -e 1e-9 [dataset_filename]
  • simultaneous safe screeing: ./test/elastic_smooth_module -s 15 -e 1e-9 - d 1 [dataset_filename]
  • safe feature screeing: ./test/elastic_smooth_module -s 16 -e 1e-9 -d 1 [dataset_filename]
  • safe sample screeing: ./test/elastic_smooth_module -s 17 -e 1e-9 - d 1 [dataset_filename]

###Elastic net + smoothed epsilon-insensitive loss (model selection task) with SPDC

  • non-screeing: ./test/elastic_soft_module -s 14 -e 1e-9 [dataset_filename]
  • simultaneous safe screeing: ./test/elastic_soft_module -s 15 -e 1e-9 - d 1 [dataset_filename]
  • safe feature screeing: ./test/elastic_soft_module -s 16 -e 1e-9 -d 1 [dataset_filename]
  • safe sample screeing: ./test/elastic_soft_module -s 17 -e 1e-9 - d 1 [dataset_filename]

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