| Hybrid Block Successive Approximation for One-Sided Non-Convex Min-max Problems: Algorithms and Applications S Lu, I Tsaknakis, M Hong, Y Chen IEEE Transactions on Signal Processing 68, 3676-3691, 2020 | 238 | 2020 |
| Nonconvex min-max optimization: Applications, challenges, and recent theoretical advances M Razaviyayn, T Huang, S Lu, M Nouiehed, M Sanjabi, M Hong IEEE Signal Processing Magazine 37 (5), 55-66, 2020 | 180 | 2020 |
| Decentralized federated learning for electronic health records S Lu, Y Zhang, Y Wang 2020 54th Annual Conference on Information Sciences and Systems (CISS), 1-5, 2020 | 142* | 2020 |
| Distributed Learning in the Nonconvex World: From batch data to streaming and beyond TH Chang, M Hong, HT Wai, X Zhang, S Lu IEEE Signal Processing Magazine 37 (3), 26-38, 2020 | 124 | 2020 |
| Min-max optimization without gradients: Convergence and applications to black-box evasion and poisoning attacks S Liu, S Lu, X Chen, Y Feng, K Xu, A Al-Dujaili, M Hong, UM O’Reilly International Conference on Machine Learning (ICML), 6282-6293, 2020 | 105 | 2020 |
| Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning S Lu, K Zhang, T Chen, T Basar, L Horesh Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 8767-8775, 2021 | 102 | 2021 |
| GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized Optimization S Lu, X Zhang, H Sun, M Hong 2019 IEEE Data Science Workshop (DSW), 315-321, 2019 | 99 | 2019 |
| Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking H Sun, S Lu, M Hong International Conference on Machine Learning (ICML), 9217-9228, 2020 | 92 | 2020 |
| ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training CY Chen, J Ni, S Lu, X Cui, PY Chen, X Sun, N Wang, S Venkataramani, ... Advances in Neural Information Processing Systems (NeurIPS) 33, 2020 | 90 | 2020 |
| Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization Z Li, PY Chen, S Liu, S Lu, Y Xu International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021 | 74 | 2021 |
| Federated acoustic modeling for automatic speech recognition X Cui, S Lu, B Kingsbury ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 64 | 2021 |
| How Do Nonlinear Transformers Learn and Generalize in In-Context Learning? H Li, M Wang, S Lu, X Cui, PY Chen Forty-first International Conference on Machine Learning (ICML), 2024 | 63* | 2024 |
| Byzantine-Robust Decentralized Federated Learning M Fang, Z Zhang, Hairi, P Khanduri, J Liu, S Lu, Y Liu, N Gong ACM Conference on Computer and Communications Security (CCS), 2024 | 61 | 2024 |
| A Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization: Convergence Analysis and Optimality S Lu, M Hong, Z Wang IEEE Transactions on Signal Processing 65 (12), 3120–3135, 2017 | 60 | 2017 |
| An Efficient Learning Framework For Federated XGBoost Using Secret Sharing and Distributed Optimization L Xie, J Liu, S Lu, TH Chang, Q Shi ACM Transactions on Intelligent Systems and Technology (TIST) 13 (5), 2022 | 58 | 2022 |
| On the Convergence and Sample Complexity Analysis of Deep Q-Networks with -Greedy Exploration S Zhang, H Li, M Wang, M Liu, PY Chen, S Lu, S Liu, K Murugesan, ... Advances in Neural Information Processing Systems (NeurIPS) 36, 2024 | 53 | 2024 |
| A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization S Lu, S Zeng, X Cui, M Squillante, L Horesh, B Kingsbury, J Liu, M Hong Advances in Neural Information Processing Systems (NeurIPS), 2022 | 50* | 2022 |
| Understanding latent correlation-based multiview learning and self-supervision: An identifiability perspective Q Lyu, X Fu, W Wang, S Lu International Conference on Learning Representations (ICLR), 2022 | 47 | 2022 |
| Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis G Wang, S Lu, G Giannakis, G Tesauro, J Sun Advances in Neural Information Processing Systems (NeurIPS) 33, 2020 | 46 | 2020 |
| Block alternating optimization for non-convex min-max problems: algorithms and applications in signal processing and communications S Lu, I Tsaknakis, M Hong ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 44 | 2019 |
Mingyi HongAssociate Professor, University of Minnesota; Amazon AGIVerified email at umn.edu
