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Homotopy Parametric Simplex Method for Sparse Learning
High dimensional sparse learning has imposed a great computational challenge to large scale data analysis.
Optimization for Compressed Sensing: the Simplex Method and Kronecker Sparsification
For the first approach, we note that the zero vector can be taken as the initial basic (infeasible) solution for the linear programming problem and therefore, if the true signal is very sparse, some variants of the simplex method can be expected to take only a small number of pivots to arrive at a solution.
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