【文献梳理】稀疏表示优化求解:从凸优化到深度展开

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参考文献: [1] Daubechies I, Defrise M, De Mol C. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint[J]. Commun. Pur. Appl. Math., 2004, 57(11): 1413-1457. [2] Hunter D R, Lange K. A tutorial on MM algorithms[J]. The American Statistician, 2004, 58(1): 30-37. [3] Landweber L. An iteration formula for Fredholm integral equations of the first kind[J]. American Journal of Mathematics, 1951, 73(3): 615-624. [4] Beck A, Teboulle M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems[J]. SIAM Journal on Imaging Sciences, 2009, 2(1): 183-202. [5] Attouch H, Peypouquet J. The rate of convergence of Nesterov's accelerated forward-backward method is actually faster than 1/k^2[J]. SIAM Journal on Optimization, 2016, 26(3): 1824-1834. [6] Gregor K, LeCun Y. Learning fast approximations of sparse coding[C]//Proceedings of the 27th international conference on machine learning. 2010: 399-406. [7] Zhang J, Ghanem B. ISTA-Net: Interpretable optimization-inspired deep network for image compressive sensing[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 1828-1837. 最后有一点口误,Identify Mapping 的 Loss 那边是对 GT 做的,不是 Pred
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