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2020 – today
- 2024
[j9]Antonin Chambolle, Claire Delplancke, Matthias J. Ehrhardt
, Carola-Bibiane Schönlieb, Junqi Tang:
Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes. J. Math. Imaging Vis. 66(3): 294-313 (2024)- [j8]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Provably Convergent Plug-and-Play Quasi-Newton Methods. SIAM J. Imaging Sci. 17(2): 785-819 (2024) - [j7]Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang:
NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems. SIAM J. Imaging Sci. 17(2): 820-860 (2024) - [j6]Derek Driggs, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang:
Practical Acceleration of the Condat-Vũ Algorithm. SIAM J. Imaging Sci. 17(4): 2076-2109 (2024) - [j5]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration. Trans. Mach. Learn. Res. 2024 (2024) - [i19]Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. CoRR abs/2404.05445 (2024) - [i18]Matthias J. Ehrhardt, Zeljko Kereta, Jingwei Liang, Junqi Tang:
A Guide to Stochastic Optimisation for Large-Scale Inverse Problems. CoRR abs/2406.06342 (2024) - [i17]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds. CoRR abs/2408.06996 (2024) - [i16]Guixian Xu, Jinglai Li, Junqi Tang:
Sketched Equivariant Imaging Regularization and Deep Internal Learning for Inverse Problems. CoRR abs/2411.05771 (2024) - 2023
- [j4]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Data-Driven Mirror Descent with Input-Convex Neural Networks. SIAM J. Math. Data Sci. 5(2): 558-587 (2023) - [j3]Bin Qian, Zhenyu Wen, Junqi Tang, Ye Yuan, Albert Y. Zomaya, Rajiv Ranjan:
OsmoticGate: Adaptive Edge-Based Real-Time Video Analytics for the Internet of Things. IEEE Trans. Computers 72(4): 1178-1193 (2023) - [c6]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Andreas Hauptmann, Carola-Bibiane Schönlieb:
Robust Data-Driven Accelerated Mirror Descent. ICASSP 2023: 1-5 - [i15]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Provably Convergent Plug-and-Play Quasi-Newton Methods. CoRR abs/2303.07271 (2023) - [i14]Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang:
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems. CoRR abs/2304.08342 (2023) - [i13]Qingping Zhou, Jiayu Qian, Junqi Tang, Jinglai Li:
Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems. CoRR abs/2307.16120 (2023) - [i12]Marcello Carioni, Subhadip Mukherjee, Hong Ye Tan, Junqi Tang:
Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging. CoRR abs/2311.08972 (2023) - 2022
- [i11]Junqi Tang:
Equivariance Regularization for Image Reconstruction. CoRR abs/2202.05062 (2022) - [i10]Junqi Tang:
Data-Consistent Local Superresolution for Medical Imaging. CoRR abs/2202.10875 (2022) - [i9]Junqi Tang:
Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients. CoRR abs/2203.07308 (2022) - [i8]Junqi Tang:
Operator Sketching for Deep Unrolling Networks. CoRR abs/2203.11156 (2022) - [i7]Junqi Tang, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb:
Stochastic Primal-Dual Three Operator Splitting with Arbitrary Sampling and Preconditioning. CoRR abs/2208.01631 (2022) - [i6]Junqi Tang, Subhadip Mukherjee, Carola-Bibiane Schönlieb:
Accelerating Deep Unrolling Networks via Dimensionality Reduction. CoRR abs/2208.14784 (2022) - 2021
- [j2]Derek Driggs, Junqi Tang, Jingwei Liang, Mike E. Davies, Carola-Bibiane Schönlieb:
A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization. SIAM J. Imaging Sci. 14(4): 1932-1970 (2021) - [c5]Julián Tachella, Junqi Tang, Mike E. Davies:
The Neural Tangent Link Between CNN Denoisers and Non-Local Filters. CVPR 2021: 8618-8627 - [i5]Junqi Tang:
Stochastic Primal-Dual Deep Unrolling Networks for Imaging Inverse Problems. CoRR abs/2110.10093 (2021) - 2020
- [j1]Junqi Tang, Karen O. Egiazarian, Mohammad Golbabaee, Mike E. Davies:
The Practicality of Stochastic Optimization in Imaging Inverse Problems. IEEE Trans. Computational Imaging 6: 1471-1485 (2020) - [i4]Julián Tachella, Junqi Tang, Mike E. Davies:
CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser. CoRR abs/2006.02379 (2020) - [i3]Junqi Tang, Mike E. Davies:
A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problems. CoRR abs/2006.11630 (2020)
2010 – 2019
- 2019
- [b1]Junqi Tang:
Randomized structure-adaptive optimization. University of Edinburgh, UK, 2019 - [c4]Junqi Tang, Karen O. Egiazarian, Mike E. Davies:
The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems. ICASSP 2019: 7680-7684 - [i2]Junqi Tang, Karen O. Egiazarian, Mohammad Golbabaee, Mike E. Davies:
The Practicality of Stochastic Optimization in Imaging Inverse Problems. CoRR abs/1910.10100 (2019) - 2018
- [c3]Junqi Tang, Mohammad Golbabaee, Francis R. Bach, Mike E. Davies:
Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes. NeurIPS 2018: 427-438 - 2017
- [c2]Junqi Tang, Mohammad Golbabaee, Mike E. Davies:
Exploiting the structure via sketched gradient algorithms. GlobalSIP 2017: 1305-1309 - [c1]Junqi Tang, Mohammad Golbabaee, Mike E. Davies:
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares. ICML 2017: 3377-3386 - 2016
- [i1]Junqi Tang:
The Non-uniform Fast Fourier Transform in Computed Tomography. CoRR abs/1605.05231 (2016)
Coauthor Index
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