Junqi Tang

According to our database, Junqi Tang authored at least 32 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes.

Antonin Chambolle, Claire Delplancke, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang

J. Math. Imaging Vis., June, 2024

Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration.

Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb

Trans. Mach. Learn. Res., 2024

Provably Convergent Plug-and-Play Quasi-Newton Methods.

Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb

SIAM J. Imaging Sci., 2024

Practical Acceleration of the Condat-Vũ Algorithm.

Derek Driggs, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang

SIAM J. Imaging Sci., 2024

NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems.

Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang

SIAM J. Imaging Sci., 2024

Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds.

Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb

CoRR, 2024

A Guide to Stochastic Optimisation for Large-Scale Inverse Problems.

Matthias J. Ehrhardt, Zeljko Kereta, Jingwei Liang, Junqi Tang

CoRR, 2024

Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation.

Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb

CoRR, 2024

2023

Data-Driven Mirror Descent with Input-Convex Neural Networks.

Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb

SIAM J. Math. Data Sci., June, 2023

OsmoticGate: Adaptive Edge-Based Real-Time Video Analytics for the Internet of Things.

Bin Qian, Zhenyu Wen, Junqi Tang, Ye Yuan, Albert Y. Zomaya, Rajiv Ranjan

IEEE Trans. Computers, April, 2023

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

Marcello Carioni, Subhadip Mukherjee, Hong Ye Tan, Junqi Tang

CoRR, 2023

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

Qingping Zhou, Jiayu Qian, Junqi Tang, Jinglai Li

CoRR, 2023

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

Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang

CoRR, 2023

Robust Data-Driven Accelerated Mirror Descent.

Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Andreas Hauptmann, Carola-Bibiane Schönlieb

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Accelerating Deep Unrolling Networks via Dimensionality Reduction.

Junqi Tang, Subhadip Mukherjee, Carola-Bibiane Schönlieb

CoRR, 2022

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

Junqi Tang, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb

CoRR, 2022

Operator Sketching for Deep Unrolling Networks.

Junqi Tang

CoRR, 2022

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

Junqi Tang

CoRR, 2022

Data-Consistent Local Superresolution for Medical Imaging.

Junqi Tang

CoRR, 2022

Equivariance Regularization for Image Reconstruction.

Junqi Tang

CoRR, 2022

2021

A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization.

Derek Driggs, Junqi Tang, Jingwei Liang, Mike E. Davies, Carola-Bibiane Schönlieb

SIAM J. Imaging Sci., 2021

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

Junqi Tang

CoRR, 2021

The Neural Tangent Link Between CNN Denoisers and Non-Local Filters.

Julián Tachella, Junqi Tang, Mike E. Davies

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

The Practicality of Stochastic Optimization in Imaging Inverse Problems.

Junqi Tang, Karen O. Egiazarian, Mohammad Golbabaee, Mike E. Davies

IEEE Trans. Computational Imaging, 2020

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

Junqi Tang, Mike E. Davies

CoRR, 2020

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

Julián Tachella, Junqi Tang, Mike E. Davies

CoRR, 2020

2019

Randomized structure-adaptive optimization.

Junqi Tang

PhD thesis, 2019

The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems.

Junqi Tang, Karen O. Egiazarian, Mike E. Davies

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes.

Junqi Tang, Mohammad Golbabaee, Francis R. Bach, Mike E. Davies

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.

Junqi Tang, Mohammad Golbabaee, Mike E. Davies

Proceedings of the 34th International Conference on Machine Learning, 2017

Exploiting the structure via sketched gradient algorithms.

Junqi Tang, Mohammad Golbabaee, Mike E. Davies

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016

The Non-uniform Fast Fourier Transform in Computed Tomography.

Junqi Tang

CoRR, 2016