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L1 Minimization is a Mathematical optimization technique used to promote Sparsity in solutions, making it particularly useful in fields such as Compressed Sensing and Machine Learning. By minimizing the L1 Norm of a vector, it effectively reduces the number of Non-zero elements, providing a robust method for Feature Selection and Noise Reduction in High-dimensional data sets.
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