Qing Qu

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Can we recover a complex signal from its Fourier magnitudes? More generally, given a set of m measurements, y k = |a * k x| for k = 1,. .. , m, is it possible to recover x ∈ C n (i.e., length-n complex vector)? This generalized phase retrieval (GPR) problem is a fundamental task in various disciplines, and has been the subject of much recent investigation.(More)
We consider the problem of recovering the sparsest vector in a subspace S ∈ R p with dim (S) = n. This problem can be considered a homogeneous variant of the sparse recovery problem, and finds applications in sparse dictionary learning, sparse PCA, and other problems in signal processing and machine learning. Simple convex heuristics for this problem(More)
—Pixel-wise classification, where each pixel is assigned to a predefined class, is one of the most important procedures in hyperspectral image (HSI) analysis. By representing a test pixel as a linear combination of a small subset of labeled pixels, a sparse representation classifier (SRC) gives rather plausible results compared with that of traditional(More)
We consider the problem of recovering a complete (i.e., square and invertible) matrix A 0 , from Y ∈ R n×p with Y = A 0 X 0 , provided X 0 is sufficiently sparse. This recovery problem is central to the theoretical understanding of dictionary learning, which seeks a sparse representation for a collection of input signals, and finds numerous applications in(More)
We consider the problem of recovering a complete (i.e., square and invertible) matrix A 0 , from Y ∈ R n×p with Y = A 0 X 0 , provided X 0 is sufficiently sparse. This recovery problem is central to theoretical understanding of dictionary learning, which seeks a sparse representation for a collection of input signals and finds numerous applications in(More)
Recent studies have highlighted the role of androgen receptor (AR) as a prognostic biomarker of breast cancer. However, its predictive role in disease free survival (DFS) and overall survival (OS) still remains inconclusive. The present study aimed to retrospectively investigate the association between AR and survival outcomes in breast cancer and also(More)