Research output per year
Research output per year
- 21 results
Search results
-
2025
A Guide to Stochastic Optimisation for Large-Scale Inverse Problems
Ehrhardt, M. J., Kereta, Ž., Liang, J. & Tang, J., 15 May 2025, In: Inverse Problems. 41, 5, 61 p., 053001.Research output: Contribution to journal › Article › peer-review
Open AccessFile24 Downloads (Pure) -
Iterative Operator Sketching Framework for Large-Scale Imaging Inverse Problems
Tang, J., Mukherjee, S. & Schönlieb, C.-B., 7 Mar 2025, ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, p. 1-5 5 p. (International Conference on Acoustics, Speech, and Signal Processing (ICASSP)).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile9 Downloads (Pure) -
Stochastic Primal-Dual Three Operator Splitting Algorithm with Extension to Equivariant Regularization-by-Denoising
Tang, J., Ehrhardt, M. J. & Schönlieb, C.-B., 17 May 2025, Scale Space and Variational Methods in Computer Vision: 10th International Conference, SSVM 2025, Dartington, UK, May 18–22, 2025, Proceedings, Part II. Bubba, T. A., Gaburro, R., Gazzola, S., Papafitsoros, K., Pereyra, M. & Schönlieb, C.-B. (eds.). 1 ed. Springer, p. 30-41 11 p. (Lecture Notes in Computer Science; vol. 15668).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Downloads (Pure) -
2024
Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration
Tan, H. Y., Mukherjee, S., Tang, J. & Schönlieb, C.-B., 16 May 2024, In: Transactions on Machine Learning Research.Research output: Contribution to journal › Article › peer-review
Open Access -
Deep unrolling networks with recurrent momentum acceleration for nonlinear inverse problems
Zhou, Q., Qian, J., Tang, J. & Li, J., May 2024, In: Inverse Problems. 40, 5, 20 p., 055014.Research output: Contribution to journal › Article › peer-review
Open AccessFile130 Downloads (Pure) -
NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems
Cai, Z., Tang, J., Mukherjee, S., Li, J., Schönlieb, C.-B. & Zhang, X., 8 Apr 2024, In: SIAM Journal on Imaging Sciences. 17, 2, p. 820-860 41 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile246 Downloads (Pure) -
Practical Acceleration of the Condat–Vũ Algorithm
Driggs, D., Ehrhardt, M., Schönlieb, C.-B. & Tang, J., 10 Jul 2024, (Accepted/In press) In: SIAM Journal on Imaging Sciences.Research output: Contribution to journal › Article › peer-review
Open AccessFile121 Downloads (Pure) -
Provably Convergent Plug-and-Play Quasi-Newton Methods
Tan, H. Y., Mukherjee, S., Tang, J. & Schönlieb, C.-B., 2 Apr 2024, In: SIAM Journal on Imaging Sciences. 17, 2, p. 785-819Research output: Contribution to journal › Article › peer-review
Open AccessFile90 Downloads (Pure) -
Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes
Chambolle, A., Delplancke, C., Ehrhardt, M., Schönlieb, C.-B. & Tang, J., 16 Mar 2024, (E-pub ahead of print) In: Journal of Mathematical Imaging and Vision.Research output: Contribution to journal › Article › peer-review
Open AccessFile105 Downloads (Pure) -
Unsupervised Approaches Based on Optimal Transport and Convex Analysis for Inverse Problems in Imaging
Carioni, M., Mukherjee, S., Tan, H. Y. & Tang, J., 18 Nov 2024, Data-driven Models in Inverse Problems. Bubba, T. A. (ed.). De Gruyter, p. 107-162 57 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review
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Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
Tan, H. Y., Cai, Z., Pereyra, M., Mukherjee, S., Tang, J. & Schönlieb, C.-B., 13 Dec 2024, In: Transactions on Machine Learning Research. 28 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile8 Downloads (Pure) -
2023
Data-Driven Mirror Descent with Input-Convex Neural Networks
Tan, H. Y., Mukherjee, S., Tang, J. & Schönlieb, C.-B., 30 Jun 2023, In: SIAM Journal on Mathematics of Data Science. 5, 2, p. 558-587Research output: Contribution to journal › Article › peer-review
Open AccessFile87 Downloads (Pure) -
OsmoticGate: Adaptive Edge-based Real-time Video Analytics for the Internet of Things
Qian, B., Wen, Z., Tang, J., Yuan, Y., Zomaya, A. & Ranjan, R., Apr 2023, In: IEEE Transactions on Computers. 72, 4, p. 1178-1193 16 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile90 Downloads (Pure) -
Robust Data-Driven Accelerated Mirror Descent
Tan, H. Y., Mukherjee, S., Tang, J., Hauptmann, A. & Schönlieb, C.-B., 5 May 2023, (E-pub ahead of print) ICASSP 2023 - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEEResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile41 Downloads (Pure) -
2021
A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization
Driggs, D., Tang, J., Liang, J., Davies, M. & Schönlieb, C.-B., 21 Dec 2021, In: SIAM Journal on Imaging Sciences. 14, 4, p. 1932-1970 39 p.Research output: Contribution to journal › Article › peer-review
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The Neural Tangent Link Between CNN Denoisers and Non-Local Filters
Tachella, J., Tang, J. & Davies, M., 2 Nov 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, p. 8614-8623 10 p. 9578172. (Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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2020
The Practicality of Stochastic Optimization in Imaging Inverse Problems
Tang, J., Egiazarian, K., Golbabaee, M. & Davies, M., 21 Oct 2020, In: IEEE Transactions on Computational Imaging.Research output: Contribution to journal › Article › peer-review
Open Access -
2019
The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems
Tang, J., Egiazarian, K. & Davies, M., 12 May 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access -
2018
Rest-Katyusha: Exploiting the Solution’s Structure via Scheduled Restart Schemes
Tang, J., Golbabaee, M., Bach, F. & Davies, M., 3 Dec 2018, Advances in Neural Information Processing Systems 31 (NeurIPS 2018).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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2017
Exploiting the structure via sketched gradient algorithms
Tang, J., Golbabaee, M. & Davies, M., 14 Nov 2017, 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access -
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
Tang, J., Golbabaee, M. & Davies, M., 6 Aug 2017, Proceedings of the 34th International Conference on Machine Learning.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution