Solving Sparse Linear Inverse Problems in Communication Systems: A Deep
Learning Approach With Adaptive Depth

Solving Sparse Linear Inverse Problems in Communication Systems: A Deep Learning Approach With Adaptive Depth

29 October 2020

Papers citing "Solving Sparse Linear Inverse Problems in Communication Systems: A Deep Learning Approach With Adaptive Depth"

11 / 11 papers shown

Title
Deep Learning Methods for Solving Linear Inverse Problems: Research Directions and Paradigms Yanna Bai Wei Chen Jie Chen Weisi Guo 75 67 0 27 Jul 2020
Learning step sizes for unfolded sparse coding Pierre Ablin Thomas Moreau Mathurin Massias Alexandre Gramfort MQ 58 53 0 27 May 2019
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds Xiaohan Chen Jialin Liu Zhangyang Wang W. Yin 58 233 0 29 Aug 2018
From Bayesian Sparsity to Gated Recurrent Nets Hao He Bo Xin David Wipf BDL 36 36 0 09 Jun 2017
Spatially Adaptive Computation Time for Residual Networks Michael Figurnov Maxwell D. Collins Yukun Zhu Li Zhang Jonathan Huang Dmitry Vetrov Ruslan Salakhutdinov 58 347 0 07 Dec 2016
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 99 2,004 0 14 Jun 2016
Maximal Sparsity with Deep Networks? Bo Xin Yizhou Wang Wen Gao David Wipf 3DPC 67 167 0 05 May 2016
Adaptive Computation Time for Recurrent Neural Networks Alex Graves 88 6 0 29 Mar 2016
Learning optimal nonlinearities for iterative thresholding algorithms Ulugbek S. Kamilov Hassan Mansour 44 108 0 15 Dec 2015
Sharp Time--Data Tradeoffs for Linear Inverse Problems Samet Oymak Benjamin Recht Mahdi Soltanolkotabi 68 88 0 16 Jul 2015
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures J. Hershey Jonathan Le Roux F. Weninger BDL 98 430 0 09 Sep 2014