Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 9 of 9 for “"sparse vector"”.
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Fast superresolution based on a network structure trained using sparse coding
… to superresolution using a network structure. Sparse representation of image signals forms the cornerstone of our approach and the goal is to obtain resolution enhancement of the low resolution images. I will discuss various dictionary learning methods and also a joint dictionary training …
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Sparse Solutions to Structured Underdetermined Systems in the Presence of Small Noise
… of the number of nonzero entries of our unknown sparse vector, as well as an upper bound on the magnitude of the small noise to guarantee the correct localization of these nonzero entries. Simulations suggest that the first bound is very tight and that the two proposed algorithms outperform …
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Sparse recovery and Fourier sampling
… decade a broad literature has arisen studying sparse recovery, the estimation of sparse vectors from low dimensional linear projections. Sparse recovery has a wide variety of applications such as streaming algorithms, image acquisition, and disease testing. A particularly important subclass of …
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Automated methods for checking differential privacy
… response, histogram, report noisy max and sparse vector.
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A spin on compressive sensing imaging : reticle-based single-pixel imaging system
… is a signal acquisition technique to recover a sparse vector from only a few linear measurements. CS assumes a sparse vector being sampled and the use of sparsifying dictionaries is required for sampling non-sparse vectors such as images. Optimizing the sensing matrix to improve the recovery …
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Efficient and guaranteed algorithms for sparse inverse problems
… and reduced-cost acquisition, by exploiting a sparse signal model. Most notably, recovery of the signal by computationally efficient algorithms is guaranteed for certain randomized acquisition systems. However, there is a discrepancy between the theoretical guarantees and practical …
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Differentially private data publishing for data analysis
… DPLloyd and EUGkM. Finally, we investigate the sparse vector technique (SVT) which is a fundamental technique for satisfying differential privacy in answering a sequence of queries. We propose a new version of SVT that provides better utility by introducing an effective technique to improve the …
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Power grid verification and optimization
… memory system. Advanced techniques such as sparse vector and solution mapping are developed or utilized to accelerate the forward and backward substitutions in each time step. Multiple threads are utilized to further reduce runtime. As the first-place winner in the ``TAU_2012 power grid …
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Algorithms and lower bounds in the streaming and sparse recovery models
… for each possible item we might see. In the sparse recovery model (also known as compressed sensing), input data is a large but sparse vector x [epsilon] Rn, and our goal is to design an m x n matrix [Phi]D, where m << n, such that for any sufficiently sparse x we can efficiently recover a …