Junqi (Billy) Tang
Dr Junqi (Billy) Tang, Assistant Professor.
邮件:j.tang.2@bham.ac.uk
PhD, University of Edinburgh, 2019
Dr Junqi (Billy) Tang is an Assistant Professor in Mathematical Optimisation and Data Science in the School of Mathematics, where he has been based since Spring 2023.
His research interests include large-scale optimisation and learning theory, with applications in data science. Most recently, his research has been focusing on the theoretical foundations of non-convex optimisation in machine learning, data-driven optimisation, and efficient deep unrolling networks in computational imaging.
Article
Tan, HY, Mukherjee, S, Tang, J & Schönlieb, C-B 2023, 'Data-Driven Mirror Descent with Input-Convex Neural Networks', SIAM Journal on Mathematics of Data Science, vol. 5, no. 2, pp. 558-587. https://doi.org/
Qian, B, Wen, Z, Tang, J, Yuan, Y, Zomaya, A & Ranjan, R 2023, 'OsmoticGate: Adaptive Edge-based Real-time Video Analytics for the Internet of Things', IEEE Transactions on Computers, vol. 72, no. 4, pp. 1178-1193. https://doi.org/
Driggs, D, Tang, J, Liang, J, Davies, M & Schönlieb, C-B 2021, 'A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization', SIAM Journal on Imaging Sciences, vol. 14, no. 4, pp. 1932-1970. https://doi.org/
Tang, J, Egiazarian, K, Golbabaee, M & Davies, M 2020, 'The Practicality of Stochastic Optimization in Imaging Inverse Problems', IEEE Transactions on Computational Imaging. https://doi.org/
Conference contribution
Tan, HY, Mukherjee, S, Tang, J, Hauptmann, A & Schönlieb, C-B 2023, Robust Data-Driven Accelerated Mirror Descent. in ICASSP 2023 - IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Greece, 4/
Tachella, J, Tang, J & Davies, M 2021, The Neural Tangent Link Between CNN Denoisers and Non-Local Filters. in 2021 IEEE/
Tang, J, Egiazarian, K & Davies, M 2019, The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems. in ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). https://doi.org/
Tang, J, Golbabaee, M, Bach, F & Davies, M 2018, Rest-Katyusha: Exploiting the Solution’s Structure via Scheduled Restart Schemes. in Advances in Neural Information Processing Systems 31 (NeurIPS 2018). <https://proceedings.neurips.cc/
Tang, J, Golbabaee, M & Davies, M 2017, Exploiting the structure via sketched gradient algorithms. in 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP). https://doi.org/
Tang, J, Golbabaee, M & Davies, M 2017, Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares. in Proceedings of the 34th International Conference on Machine Learning. <http://proceedings.mlr.press/