in Seminar Inverse Problem Deep Learning Compressed Sensing Optimization ~ read.

[TBD] Imaging And Graphics Seminar

Topic: Sparse Iterating Algorithm And Deep Learning.

Hold: Yiping Lu

On the Convergence of Learning-based Iterative
Methods for Nonconvex Inverse Problems
Risheng Liu, Member, IEEE, Shichao Cheng, Yi He, Xin Fan, Member, IEEE, Zhouchen Lin, Fellow, IEEE,
and Zhongxuan Luo

Theoretical linear convergence of unfolded ISTA and its practial weight and thresholds
Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin

Hao He, Bo Xin, Satoshi Ikehata, and David Wipf, "From Bayesian Sparsity to Gated Recurrent Nets," Advances in Neural Information Processing Systems (NIPS), 2017.

Bo Xin, Yizhou Wang, Wen Gao, Baoyuan Wang, and David Wipf, "Maximal Sparsity with Deep Networks?," Advances in Neural Information Processing Systems (NIPS), 2016.

Bora, Ashish, et al. "Compressed sensing using generative models." arXiv preprint arXiv:1703.03208 (2017).

Kabkab, Maya, Pouya Samangouei, and Rama Chellappa. "Task-Aware Compressed Sensing with Generative Adversarial Networks." arXiv preprint arXiv:1802.01284 (2018).

Van Veen, David, et al. "Compressed Sensing with Deep Image Prior and Learned Regularization." arXiv preprint arXiv:1806.06438 (2018).