A single-loop smoothed gradient descent-ascent algorithm for nonconvex-concave min-max problems J Zhang, P Xiao, R Sun, Z Luo Advances in neural information processing systems 33, 7377-7389, 2020 | 83 | 2020 |
A proximal alternating direction method of multiplier for linearly constrained nonconvex minimization J Zhang, ZQ Luo SIAM Journal on Optimization 30 (3), 2272-2302, 2020 | 75 | 2020 |
A global dual error bound and its application to the analysis of linearly constrained nonconvex optimization J Zhang, ZQ Luo SIAM Journal on Optimization 32 (3), 2319-2346, 2022 | 36 | 2022 |
Distributed stochastic consensus optimization with momentum for nonconvex nonsmooth problems Z Wang, J Zhang, TH Chang, J Li, ZQ Luo IEEE Transactions on Signal Processing 69, 4486-4501, 2021 | 27 | 2021 |
Revisiting the linear-programming framework for offline rl with general function approximation AE Ozdaglar, S Pattathil, J Zhang, K Zhang International Conference on Machine Learning, 26769-26791, 2023 | 16 | 2023 |
Communication efficient primal-dual algorithm for nonconvex nonsmooth distributed optimization C Chen, J Zhang, L Shen, P Zhao, Z Luo International Conference on Artificial Intelligence and Statistics, 1594-1602, 2021 | 14 | 2021 |
What is a Good Metric to Study Generalization of Minimax Learners? A Ozdaglar, S Pattathil, J Zhang, K Zhang Advances in Neural Information Processing Systems 35, 38190-38203, 2022 | 10 | 2022 |
When Expressivity Meets Trainability: Fewer than Neurons Can Work J Zhang, Y Zhang, M Hong, R Sun, ZQ Luo Advances in Neural Information Processing Systems 34, 9167-9180, 2021 | 8 | 2021 |
Linearly constrained bilevel optimization: A smoothed implicit gradient approach P Khanduri, I Tsaknakis, Y Zhang, J Liu, S Liu, J Zhang, M Hong International Conference on Machine Learning, 16291-16325, 2023 | 7 | 2023 |
On the iteration complexity of smoothed proximal alm for nonconvex optimization problem with convex constraints J Zhang, W Pu, ZQ Luo arXiv preprint arXiv:2207.06304, 2022 | 6 | 2022 |
Decentralized Non-Convex Learning With Linearly Coupled Constraints: Algorithm Designs and Application to Vertical Learning Problem J Zhang, S Ge, TH Chang, ZQ Luo IEEE Transactions on Signal Processing 70, 3312-3327, 2022 | 5 | 2022 |
A proximal dual consensus method for linearly coupled multi-agent non-convex optimization J Zhang, S Ge, TH Chang, ZQ Luo ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 4 | 2020 |
Characterization of SINR region for multi-cell downlink NOMA systems X Zhang, Y Chen, J Zhang, Y Lei, C Shen, G Zhu ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-6, 2019 | 4 | 2019 |
Decentralized non-convex learning with linearly coupled constraints J Zhang, S Ge, TH Chang, ZQ Luo arXiv preprint arXiv:2103.05378, 2021 | 3 | 2021 |
Exact O(N2) Hyper-Parameter Optimization for Gaussian Process Regression L Xu, Y Dai, J Zhang, C Zhang, F Yin 2020 IEEE 30th International Workshop on Machine Learning for Signal …, 2020 | 3 | 2020 |
Scalable Gaussian process using inexact ADMM for big data Y Xu, F Yin, J Zhang, W Xu, S Cui, ZQ Luo ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 2 | 2019 |
The Power of Duality Principle in Offline Average-Reward Reinforcement Learning A Ozdaglar, S Pattathil, J Zhang, K Zhang | | |