Global ETD Search
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Showing 1 to 8 of 8 for “"restricted isometry"”.
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Efficient and guaranteed algorithms for sparse inverse problems
… guarantees are derived using a so-called restricted isometry property (RIP), which has only been shown to hold under ideal assumptions. For example, the sampling from the frame needs to be independent and identically distributed with the uniform distribution, and the frame must be tight. …
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Spectral methods and computational trade-offs in high-dimensional statistical inference
… trade-offs also exist in the problem of restricted isometry certification. Certifiers for restricted isometry properties can be used to construct design matrices for sparse linear regression problems. Similar to the sparse PCA problem, we show that there is also an intrinsic gap between …
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Computable Performance Analysis of Recovering Signals with Low-dimensional Structures
… parallel to the probabilistic analysis of the restricted isometry property. Numerical experiments show that, compared with the restricted isometry based performance bounds, our error bounds apply to a wider range of problems and are tighter, when the sparsity levels of the signals are …
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Nuclear norm penalized LAD estimator for low rank matrix recovery
… using E-net covering argument under certain restricted isometry and restricted eigenvalue assumptions. The estimator is able to recover the underlying matrix with high probability with limited observations that the number of observation is more than the degree of freedom but less than a power …
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Additive Lebesgue-Type Inequalities for Greedy Approximation
… that under conditions of mutual coherence or restricted isometry property, our greedy algorithms output a result that is almost as good as the best possible.</p>
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Super Greedy Type Algorithms and Applications In Compressed Sensing
… of there two algorithms are analyzed under Restricted Isometry Property (RIP) conditions.</p>
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Informative sensing : theory and applications
… pursue the InfoMax principle, rather than the restricted isometry property, in optimizing the sensors. By approximate analysis on sparse signals, we found random projections, typical in the compressed sensing literature, to be InfoMax optimal if the sparse coefficients are independent and …
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Sparse graph codes for compression, sensing, and secrecy
… 0 or 1 have poor performance with respect to the restricted isometry property for the f2 norm. Third, we analyze the performance of a special class of sparse graph codes, LDPC codes, for the problem of quantizing a uniformly random bit string under Hamming distortion. We show that LDPC codes can …