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Songtao Lu
Songtao Lu
Assistant Professor, CSE, The Chinese University of Hong Kong
Підтверджена електронна адреса в ibm.com - Домашня сторінка
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Посилання
Посилання
Рік
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
2162020
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
1322020
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
120*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
1072020
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
962019
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
952020
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
882020
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
782020
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
742021
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
582017
Federated acoustic modeling for automatic speech recognition
X Cui, S Lu, B Kingsbury
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
522021
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
512021
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
432022
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
422019
Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems
S Lu, M Razaviyayn, B Yang, K Huang, M Hong
Advances in Neural Information Processing Systems (NeurIPS) 33, 2020
41*2020
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
40*2022
Throughput of Underwater Wireless Ad Hoc Networks with Random Access: A Physical Layer Perspective
S Lu, Z Wang, Z Wang, S Zhou
IEEE Transactions on Wireless Communications 14 (11), 6257–6268, 2015
402015
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
392022
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
382020
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
34*2024
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