We present a greedy-based approximation algorithm designed to reconstruct the vector $x$. It is applicable to matrices $A$ that satisfy the condition $\delta_{3s}\leq\frac 1{12}$. Additionally, the article includes a proof demonstrating the convergence of this algorithm.

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We explain the motivation of the Kernel method in machine learning theory and how one might go about overcoming the computational challenges.

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