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Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach

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Description

Codes for the GDT algorithm on multi-task learning

Reference

Ming Yu, Varun Gupta, and Mladen Kolar. Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach. In Electronic Journal of Statistics.

Run codes

  • Data_generation.m: generate true coefficient matrix
  • hard_thre.m: perform (row) hard thresholding on matrix
  • GDT.m: run the GDT (gradient descent with hard thresholding) algorithm

Run “Data_generation.m” to generate the data and run “GDT.m” to get the estimation.

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Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach

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