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 10 of 10 for “"Alternating minimization"”.
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Alternating Minimization Algorithms for Dual-Energy X-Ray CT Imaging and Information Optimization
… studies of the regularized alternating minimization (DE-AM) algorithm with different regularization parameters were performed to find ranges of the parameters that can achieve the desired image quality in terms of estimation accuracy and image smoothness.</p><p>The DE-AM …
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Double Alternating Minimization (DAM) for Phase Retrieval in the Presence of Poisson Noise and Pixelation
<p>Optical detectors, such as photodiodes and CMOS cameras, can only read intensity information, and thus phase information of wavefronts is lost. Phase retrieval algorithms are used to estimate the lost phase and reconstruct an accurate effective pupil function, where the squared modulus of its …
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Tomographic reconstruction with adaptive sparsifying transforms
… an adaptive sparsifying transform penalty. An alternating minimization approach is used to jointly reconstruct the image while learning a sparsifying transform adapted to the particular image being reconstructed. The Alternating Direction Method of Multipliers is used to provide a …
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Model-based methods for high-dimensional multivariate analysis
… to response category mean matrices, we use an alternating minimization algorithm that takes advantage of the Kronecker structure of the precision matrix. We show that our method can outperform relevant competitors in classification, even when our modeling assumptions are violated. We analyze an …
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Advances in Sparse and Low Rank Matrix Optimization for Machine Learning Applications
… Rank Matrix Decomposition problem. We present an alternating minimization algorithm that computes high quality feasible solutions and outperforms benchmark methods, scaling to dimension n=10000 in minutes. We additionally design a custom branch and bound algorithm to globally solve problem …
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A Multiplicative Regularisation for Inverse Problems
… regularisation model in the framework of the alternating minimisation algorithm, we were able to obtain a series of rigorous theoretical results, as well as formulating a number of new models in both multiplicative and additive form. The first two chapters of my thesis set the scene of my …
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Decay of correlations and inference in graphical models
… the Vertex Least Squares (VLS), which is same as Alternating Minimization and Edge Least Squares (ELS), which is a message-passing variation of VLS. We provide sufficient conditions on the structure of the revelation graph for IP to succeed and show that when M has rank r = 0(1), this property is …
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Semi-Supervised Learning for Scalable and Robust Visual Search
… formulation and an efficient solution via an alternating minimization procedure. Based on this bivariate framework, we also develop new methods to filter unreliable and noisy labels. Extensive experiments over diverse benchmark datasets demonstrate the superior performance of our proposed …
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Algorithms and algorithmic obstacles for probabilistic combinatorial structures
… vectors in the application of the "vanilla" alternating minimization algorithm. The structure of sparse random regular graphs is used heavily for controlling the impact of these regularization steps.
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Adaptive sparse representations and their applications
… part of this thesis, we further develop the alternating algorithms for learning unstructured (non-sparse) well-conditioned, or orthonormal square sparsifying transforms. While, in the first part of the thesis, we provided an iterative method involving conjugate gradients for the transform …