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Microsoft
Theory and Methods for Recovering Structured Patterns in High Dimensional Data
Regression with a sparsity constraint plays a vital role in many machine learning and signal processing applications. The key idea of sparsity is that only a small subset of all features are needed for good predictions. This subset is indicated by the pattern of sparsity in the regression coefficient vector. In many applications, the sparsity […]
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