—Nuclear norm minimization (NNM) has recently gained attention for its use in rank minimization problems. In this paper, we define weak, sectional and strong recovery for NNM to...
—We present an alternative analysis of weighted 1 minimization for sparse signals with a nonuniform sparsity model, and extend our results to nuclear norm minimization for matric...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
This paper proposes a novel approach for rank level fusion which gives improved performance gain verified by experimental results. In the absence of ranked features and instead of...
In this paper, we propose using Partial Differential Equation (PDE) techniques in wavelet based image processing to reduce edge artifacts generated by wavelet thresholding. We emp...