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Applications abound in which optimization problems must be repeatedly solved, each time with new (but similar) data.
Learning step sizes for unfolded sparse coding
Ablin, P.; Moreau, T.; Massias, M.; and Gramfort, A. 2019 · 1905
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Differentiable Linearized ADMM
Xie, X.; Wu, J.; Zhong, Z.; Liu, G.; and Lin, Z. 2019 · 1905
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Mean Value Methods in Iteration
Mann, R. 1953 · 1953
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Two remarks about the method of successive approximations
Krasnosel’skiĭ, M. 1955 · 1955
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A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics
Martin, D.; Fowlkes, C.; Tal, D.; and Malik, J. 2001 · 2001
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An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
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Iterative hard thresholding for compressed sensing
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Learning Fast Approximations of Sparse Coding
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Generative adversarial nets
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Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds
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Tradeoffs Between Convergence Speed and Reconstruction Accuracy in Inverse Problems
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Globally convergent type-I Anderson acceleration for non-smooth fixed-point iterations
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