Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices
Dan Yang, Zongming Ma, Andreas Buja; 17(92):1−27, 2016.
We study minimax rates for denoising simultaneously sparse and low rank matrices in high dimensions. We show that an iterative thresholding algorithm achieves (near) optimal rates adaptively under mild conditions for a large class of loss functions. Numerical experiments on synthetic datasets also demonstrate the competitive performance of the proposed method.
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