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[1] Yann LeCun,et al. Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks , 2018, ArXiv.
[2] Alexandros Georgogiannis,et al. The Generalization Error of Dictionary Learning with Moreau Envelopes , 2018, ICML.
[3] Shie Mannor,et al. The Sample Complexity of Dictionary Learning , 2010, COLT.
[4] Rémi Gribonval,et al. Dictionary Identification - Sparse Matrix-Factorisation via ℓ _ 1 -Minimisation , 2020 .
[5] J. Zico Kolter,et al. Uniform convergence may be unable to explain generalization in deep learning , 2019, NeurIPS.
[6] I. Daubechies,et al. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint , 2003, math/0307152.
[7] Ryota Tomioka,et al. In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning , 2014, ICLR.
[8] Xiaohan Chen,et al. ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA , 2018, ICLR.
[9] Nathan Srebro,et al. Exploring Generalization in Deep Learning , 2017, NIPS.
[10] Karin Schnass,et al. On the Identifiability of Overcomplete Dictionaries via the Minimisation Principle Underlying K-SVD , 2013, ArXiv.
[11] Eduardo D. Sontag,et al. Vapnik-Chervonenkis Dimension of Recurrent Neural Networks , 1997, Discret. Appl. Math..
[12] Yonina C. Eldar,et al. Performance limits of dictionary learning for sparse coding , 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).
[13] Yonina C. Eldar,et al. On the Minimax Risk of Dictionary Learning , 2015, IEEE Transactions on Information Theory.
[14] Eduardo D. Sontag,et al. Sample complexity for learning recurrent perceptron mappings , 1995, IEEE Trans. Inf. Theory.
[15] Karin Schnass,et al. Dictionary Identification—Sparse Matrix-Factorization via $\ell_1$ -Minimization , 2009, IEEE Transactions on Information Theory.
[16] Hossein Mobahi,et al. Fantastic Generalization Measures and Where to Find Them , 2019, ICLR.
[17] Xiaohan Chen,et al. Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds , 2018, NeurIPS.
[18] Yiwen Guo,et al. Sparse Coding with Gated Learned ISTA , 2020, ICLR.
[19] Yann LeCun,et al. Learning Fast Approximations of Sparse Coding , 2010, ICML.
[20] Matus Telgarsky,et al. Spectrally-normalized margin bounds for neural networks , 2017, NIPS.
[21] Michael Elad,et al. Ada-LISTA: Learned Solvers Adaptive to Varying Models , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Razvan Pascanu,et al. On the difficulty of training recurrent neural networks , 2012, ICML.
[23] Holger Rauhut,et al. A Mathematical Introduction to Compressive Sensing , 2013, Applied and Numerical Harmonic Analysis.
[24] Yi Zhang,et al. Stronger generalization bounds for deep nets via a compression approach , 2018, ICML.
[25] Mario Lezcano Casado,et al. Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group , 2019, ICML.
[26] David A. McAllester,et al. A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks , 2017, ICLR.
[27] Guillermo Sapiro,et al. Learning Efficient Sparse and Low Rank Models , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[28] M. Talagrand,et al. Probability in Banach Spaces: Isoperimetry and Processes , 1991 .
[29] Simon R. Arridge,et al. Solving inverse problems using data-driven models , 2019, Acta Numerica.
[30] Bernard Ghanem,et al. ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[31] Ben Adcock,et al. The troublesome kernel: why deep learning for inverse problems is typically unstable , 2020, ArXiv.
[32] Wen Gao,et al. Maximal Sparsity with Deep Networks? , 2016, NIPS.
[33] Pierre Vandergheynst,et al. Compressed Sensing and Redundant Dictionaries , 2007, IEEE Transactions on Information Theory.
[34] 慧 廣瀬. A Mathematical Introduction to Compressive Sensing , 2015 .
[35] Yann LeCun,et al. The mnist database of handwritten digits , 2005 .
[36] Gabriele Steidl,et al. Parseval Proximal Neural Networks , 2019, Journal of Fourier Analysis and Applications.
[37] Raja Giryes,et al. Learned Convolutional Sparse Coding , 2017, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[38] Ohad Shamir,et al. Size-Independent Sample Complexity of Neural Networks , 2017, COLT.
[39] Eduardo D. Sontag,et al. Vapnik-Chervonenkis Dimension of Recurrent Neural Networks , 1998, Discret. Appl. Math..
[40] Rémi Gribonval,et al. Sample Complexity of Dictionary Learning and Other Matrix Factorizations , 2013, IEEE Transactions on Information Theory.
[41] Andreas Maurer,et al. A Vector-Contraction Inequality for Rademacher Complexities , 2016, ALT.
[42] Hassan Mansour,et al. Learning Optimal Nonlinearities for Iterative Thresholding Algorithms , 2015, IEEE Signal Processing Letters.
[43] Shai Ben-David,et al. Understanding Machine Learning: From Theory to Algorithms , 2014 .
[44] Richard G. Baraniuk,et al. A deep learning approach to structured signal recovery , 2015, 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton).