Network pruning via performance maximization S Gao, F Huang, W Cai, H Huang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 131 | 2021 |
Discrete model compression with resource constraint for deep neural networks S Gao, F Huang, J Pei, H Huang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 86 | 2020 |
Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization F Huang, S Gao, J Pei, H Huang Journal of Machine Learning Research 23 (36), 1-70, 2022 | 76* | 2022 |
A faster decentralized algorithm for nonconvex minimax problems W Xian, F Huang, Y Zhang, H Huang Advances in Neural Information Processing Systems 34, 25865-25877, 2021 | 49 | 2021 |
Faster Adaptive Federated Learning X Wu, F Huang, Z Hu, H Huang AAAI 2023, 2023 | 46 | 2023 |
Momentum-Based Policy Gradient Methods F Huang, S Gao, J Pei, H Huang Proceedings of the 37th International Conference on Machine Learning (ICML 2020), 2020 | 45 | 2020 |
Faster stochastic alternating direction method of multipliers for nonconvex optimization F Huang, S Chen, H Huang The 36th International Conference on Machine Learning (ICML 2019), 2019 | 40 | 2019 |
Biadam: Fast adaptive bilevel optimization methods F Huang, J Li, S Gao arXiv preprint arXiv:2106.11396, 2021 | 38 | 2021 |
Faster gradient-free proximal stochastic methods for nonconvex nonsmooth optimization F Huang, B Gu, Z Huo, S Chen, H Huang Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1503-1510, 2019 | 34 | 2019 |
Efficient mirror descent ascent methods for nonsmooth minimax problems F Huang, X Wu, H Huang Advances in Neural Information Processing Systems 34, 10431-10443, 2021 | 31 | 2021 |
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients F Huang, J Li, H Huang Advances in Neural Information Processing Systems (NeurIPS) 2021, 2021 | 29 | 2021 |
Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds F Huang, S Gao IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 26 | 2023 |
Enhanced bilevel optimization via bregman distance F Huang, J Li, S Gao, H Huang Advances in Neural Information Processing Systems (NeurIPS) 2022, 2022 | 24 | 2022 |
Local stochastic bilevel optimization with momentum-based variance reduction J Li, F Huang, H Huang arXiv preprint arXiv:2205.01608, 2022 | 23 | 2022 |
Bregman Gradient Policy Optimization F Huang, S Gao, H Huang International Conference on Learning Representations (ICLR) 2022, 2022 | 21 | 2022 |
Joint learning of multiple sparse matrix Gaussian graphical models F Huang, S Chen IEEE transactions on neural networks and learning systems 26 (11), 2606-2620, 2015 | 21 | 2015 |
Accelerated Stochastic Gradient-free and Projection-free Methods F Huang, L Tao, S Chen Proceedings of the 37th International Conference on Machine Learning (ICML 2020), 2020 | 20 | 2020 |
Adagda: Faster adaptive gradient descent ascent methods for minimax optimization F Huang, X Wu, Z Hu AISTATS 2023, 2023 | 18 | 2023 |
Joint estimation of multiple conditional Gaussian graphical models F Huang, S Chen, SJ Huang IEEE transactions on neural networks and learning systems 29 (7), 3034-3046, 2017 | 17 | 2017 |
Stochastic alternating direction method of multipliers with variance reduction for nonconvex optimization F Huang, S Chen, Z Lu arXiv preprint arXiv:1610.02758, 2016 | 17 | 2016 |