A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization D Driggs, J Tang, J Liang, M Davies, CB Schönlieb SIAM Journal on Imaging Sciences 14 (4), 1932-1970, 2021 | 40* | 2021 |
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares J Tang, M Golbabaee, ME Davies ICML 2017 - International Conference on Machine Learning, 3377-3386, 2017 | 37 | 2017 |
The Practicality of Stochastic Optimization in Imaging Inverse Problems J Tang, K Egiazarian, M Golbabaee, M Davies IEEE Transactions on Computational Imaging 6, 1471-1485, 2020 | 33 | 2020 |
The Neural Tangent Link Between CNN Denoisers and Non-Local Filters J Tachella, J Tang, M Davies CVPR 2021 - IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2021 | 31* | 2021 |
Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes J Tang, M Golbabaee, F Bach, M Davies NeurIPS 2018 - Advances in Neural Information Processing Systems, 427-438, 2018 | 18 | 2018 |
Data-Driven Mirror Descent with Input-Convex Neural Networks HY Tan, S Mukherjee, J Tang, CB Schönlieb SIAM Journal on Mathematics of Data Science 5 (2), 558-587, 2023 | 14 | 2023 |
OsmoticGate: Adaptive Edge-based Real-time Video Analytics for the Internet of Things B Qian, Z Wen, J Tang, Y Yuan, A Zomaya, R Ranjan IEEE Transactions on Computers 72 (4), 1178-1193, 2023 | 14 | 2023 |
A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problems J Tang, M Davies arXiv preprint arXiv:2006.11630, 2020 | 12 | 2020 |
Accelerating Deep Unrolling Networks via Dimensionality Reduction J Tang, S Mukherjee, CB Schönlieb arXiv preprint arXiv:2208.14784, 2022 | 11* | 2022 |
The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems J Tang, K Egiazarian, M Davies ICASSP 2019 - IEEE International Conference on Acoustics, Speech and Signal …, 2019 | 8 | 2019 |
NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems Z Cai, J Tang, S Mukherjee, J Li, CB Schönlieb, X Zhang SIAM Journal on Imaging Sciences 17 (2), 820-860, 2024 | 6* | 2024 |
Provably Convergent Plug-and-Play Quasi-Newton Methods HY Tan, S Mukherjee, J Tang, CB Schönlieb SIAM Journal on Imaging Sciences 17 (2), 785--819, 2024 | 6 | 2024 |
Stochastic Primal Dual Hybrid Gradient Algorithm with Adaptive Step-Sizes A Chambolle, C Delplancke, MJ Ehrhardt, CB Schönlieb, J Tang Journal of Mathematical Imaging and Vision, 1-20, 2024 | 6 | 2024 |
Structure-Adaptive Accelerated Coordinate Descent J Tang, M Golbabaee, F Bach, M Davies Applied Inverse Problems, 2019 | 5* | 2019 |
Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems Q Zhou, J Qian, J Tang, J Li Inverse Problems 40 (5), 055014, 2024 | 4 | 2024 |
Exploiting the Structure via Sketched Gradient Algorithms J Tang, M Golbabaee, M Davies GlobalSIP 2017 - IEEE Global Conference on Signal and Information Processing …, 2017 | 4 | 2017 |
Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration HY Tan, S Mukherjee, J Tang, CB Schönlieb Transactions on Machine Learning Research, 2024 | 2 | 2024 |
Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients J Tang ICSDS-2022, 2022 | 2 | 2022 |
Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging M Carioni, S Mukherjee, HY Tan, J Tang RICAM Series, 2024 | 1 | 2024 |
Robust Data-Driven Accelerated Mirror Descent HY Tan, S Mukherjee, J Tang, A Hauptmann, CB Schönlieb ICASSP 2023 - IEEE International Conference on Acoustics, Speech and Signal …, 2023 | 1 | 2023 |