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A geometric proximal gradient method for sparse least squares regression with probabilistic simplex constraint

By Guiyun Xiao and Zheng-Jian Bai
In this paper, we consider the sparse least squares regression problem with probabilistic simplex constraint. Due to the probabilistic simplex constraint, one could not apply the L1 regularization to the considered regression model. To find a sparse solution, we reformulate the least squares regression problem as a nonconvex and nonsmooth... Show more
July 2, 2021
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A geometric proximal gradient method for sparse least squares regression with probabilistic simplex constraint
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