Junqi Tang

Orcid: 0000-0003-4996-6079

According to our database1, Junqi Tang authored at least 25 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Data-Driven Mirror Descent with Input-Convex Neural Networks.
SIAM J. Math. Data Sci., June, 2023

OsmoticGate: Adaptive Edge-Based Real-Time Video Analytics for the Internet of Things.
IEEE Trans. Computers, April, 2023

Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging.
CoRR, 2023

Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems.
CoRR, 2023

NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems.
CoRR, 2023

Provably Convergent Plug-and-Play Quasi-Newton Methods.
CoRR, 2023

Robust Data-Driven Accelerated Mirror Descent.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Accelerating Deep Unrolling Networks via Dimensionality Reduction.
CoRR, 2022

Stochastic Primal-Dual Three Operator Splitting with Arbitrary Sampling and Preconditioning.
CoRR, 2022

Operator Sketching for Deep Unrolling Networks.
CoRR, 2022

Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients.
CoRR, 2022

Data-Consistent Local Superresolution for Medical Imaging.
CoRR, 2022

Equivariance Regularization for Image Reconstruction.
CoRR, 2022

2021
A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization.
SIAM J. Imaging Sci., 2021

Stochastic Primal-Dual Deep Unrolling Networks for Imaging Inverse Problems.
CoRR, 2021

The Neural Tangent Link Between CNN Denoisers and Non-Local Filters.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
The Practicality of Stochastic Optimization in Imaging Inverse Problems.
IEEE Trans. Computational Imaging, 2020

A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problems.
CoRR, 2020

CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser.
CoRR, 2020

2019
Randomized structure-adaptive optimization.
PhD thesis, 2019

The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares.
Proceedings of the 34th International Conference on Machine Learning, 2017

Exploiting the structure via sketched gradient algorithms.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016
The Non-uniform Fast Fourier Transform in Computed Tomography.
CoRR, 2016


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