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Deep unfolding is a promising deep-learning technique in which an iterative algorithm is unrolled to a deep network architecture with trainable parameters.
Some methods of speeding up the convergence of iteration methods
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Deep unfolding: Model-based inspiration of novel deep architectures
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Analysis and design of optimization algorithms via integral quadratic constraints
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Learning to decode linear codes using deep learning
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Maximal sparsity with deep networks?
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ISTA-net: Interpretable optimization-inspired deep network for image compressive sensing
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Learning step sizes for unfolded sparse coding
P. Ablin, T. Moreau, M. Massias, and A. Gramfort · 2019
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Trainable ISTA for sparse signal recovery
D. Ito, S. Takabe, and T. Wadayama · 2019
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Physics-based learned design: Optimized coded-illumination for quantitative phase imaging
M. Kellman, E. Bostan, N. Repina, and L. Waller · 2019
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UCI machine learning repository, 2017
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Deep convolutional neural network for inverse problems in imaging
K. H. Jin, M. T. McCann, E. Froustey, and M. Unser · 2017
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Learned d-amp: Principled neural network based compressive image recovery
C. Metzler, A. Mousavi, and R. Baraniuk · 2017
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Deep mimo detection
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Deep networks for compressed image sensing
W. Shi, F. Jiang, S. Zhang, and D. Zhao · 2017
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Theoretical linear convergence of unfolded ISTA and its practical weights and thresholds
X. Chen, J. Liu, Z. Wang, and W. Yin · 2018
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M. Mardani, Q. Sun, V. Papyan, S. Vasanawala, J. Pauly, and D. Donoho · 2019
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Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing
V. Monga, Y. Li, and Y. C. Eldar · 2019
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Pytorch: An imperative style, high-performance deep learning library
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Trainable projected gradient detector for massive overloaded mimo channels: Data-driven tuning approach
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Deep learning-aided trainable projected gradient decoding for LDPC codes
T. Wadayama and S. Takabe · 2019
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Learning a compressed sensing measurement matrix via gradient unrolling
S. Wu, A. Dimakis, S. Sanghavi, F. Yu, D. Holtmann-Rice, D. Storcheus, A. Rostamizadeh, and S. Kumar · 2019
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M. Yao, J. Dang, Z. Zhang, and L. Wu · 2019
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Chebyshev inertial iteration for accelerating fixed-point iterations
T. Wadayama and S. Takabe · 2020
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Chebyshev inertial landweber algorithm for linear inverse problems
T. Wadayama and S. Takabe · 2020
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