LAG: Lazily aggregated gradient for communication-efficient distributed learning T Chen, GB Giannakis, T Sun, W Yin Advances in Neural Information Processing Systems 31, 2018 | 322 | 2018 |
Decentralized federated averaging T Sun, D Li, B Wang IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (4), 4289-4301, 2022 | 140 | 2022 |
On markov chain gradient descent T Sun, Y Sun, W Yin Advances in Neural Information Processing Systems 31, 2018 | 96 | 2018 |
NTIRE 2022 challenge on perceptual image quality assessment J Gu, H Cai, C Dong, JS Ren, R Timofte, Y Gong, S Lao, S Shi, J Wang, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 93 | 2022 |
Asynchronous Coordinate Descent under More Realistic Assumptions T Sun, R Hannah, W Yin Advances in Neural Information Processing Systems 30, 6182-6190, 2017 | 85 | 2017 |
Non-ergodic convergence analysis of heavy-ball algorithms T Sun, P Yin, D Li, C Huang, L Guan, H Jiang Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5033-5040, 2019 | 48 | 2019 |
Scheduled restart momentum for accelerated stochastic gradient descent B Wang, T Nguyen, T Sun, AL Bertozzi, RG Baraniuk, SJ Osher SIAM Journal on Imaging Sciences 15 (2), 738-761, 2022 | 42 | 2022 |
Iteratively linearized reweighted alternating direction method of multipliers for a class of nonconvex problems T Sun, H Jiang, L Cheng, W Zhu IEEE Transactions on Signal Processing 66 (20), 5380-5391, 2018 | 34 | 2018 |
Adaptive temporal difference learning with linear function approximation T Sun, H Shen, T Chen, D Li IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 28 | 2021 |
Stability and Generalization of the Decentralized Stochastic Gradient Descent T Sun, D Li, B Wang Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 35. No …, 2021 | 28 | 2021 |
Alternating direction method of multipliers with difference of convex functions T Sun, P Yin, L Cheng, H Jiang Advances in Computational Mathematics 44, 723-744, 2018 | 28 | 2018 |
Convergence of proximal iteratively reweighted nuclear norm algorithm for image processing T Sun, H Jiang, L Cheng IEEE Transactions on Image Processing 26 (12), 5632-5644, 2017 | 27 | 2017 |
Heavy-ball Algorithms Always Escape Saddle Points T Sun, D Li, Z Quan, H Jiang, S Li, Y Dou Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 21 | 2019 |
Global convergence of proximal iteratively reweighted algorithm T Sun, H Jiang, L Cheng Journal of Global Optimization, 1-12, 2017 | 21 | 2017 |
Hpdl: Towards a general framework for high-performance distributed deep learning D Li, Z Lai, K Ge, Y Zhang, Z Zhang, T Sun, Q Wang, H Wang 2019 IEEE 39th International Conference on Distributed Computing Systems …, 2019 | 19 | 2019 |
An efficient ADMM-based algorithm to nonconvex penalized support vector machines L Guan, L Qiao, D Li, T Sun, K Ge, X Lu 2018 IEEE International Conference on Data Mining Workshops (ICDMW), 1209-1216, 2018 | 18 | 2018 |
General proximal incremental aggregated gradient algorithms: Better and novel results under general scheme T Sun, Y Sun, D Li, Q Liao Advances in Neural Information Processing Systems 32, 2019 | 16 | 2019 |
On the Decentralized Stochastic Gradient Descent with Markov Chain Sampling T Sun, D Li, B Wang IEEE Transactions on Signal Processing, 2023 | 15* | 2023 |
Inertial nonconvex alternating minimizations for the image deblurring T Sun, R Barrio, M Rodríguez, H Jiang IEEE Transactions on Image Processing, 2019 | 15 | 2019 |
Training deep neural networks with adaptive momentum inspired by the quadratic optimization T Sun, H Ling, Z Shi, D Li, B Wang arXiv preprint arXiv:2110.09057, 2021 | 14 | 2021 |