Follow
Haibo Yang
Title
Cited by
Cited by
Year
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
H Yang, M Fang, J Liu
Proceedings of ICLR, 2021
2392021
Stem: A stochastic two-sided momentum algorithm achieving near-optimal sample and communication complexities for federated learning
P Khanduri, P Sharma, H Yang, M Hong, J Liu, K Rajawat, P Varshney
Advances in Neural Information Processing Systems 34, 6050-6061, 2021
652021
Anarchic Federated Learning
H Yang, X Zhang, P Khanduri, J Liu
International Conference on Machine Learning, 2022
642022
Byzantine-resilient stochastic gradient descent for distributed learning: A lipschitz-inspired coordinate-wise median approach
H Yang, X Zhang, M Fang, J Liu
2019 IEEE 58th Conference on Decision and Control (CDC), 5832-5837, 2019
422019
Over-the-Air Federated Learning with Joint Adaptive Computation and Power Control
H Yang, P Qiu, J Liu, A Yener
IEEE ISIT 2022, 2022
172022
CFedAvg: Achieving Efficient Communication and Fast Convergence in Non-IID Federated Learning
H Yang, J Liu, ES Bentley
IEEE/IFIP WiOpt 2021, 2021
172021
CHARLES: Channel-Quality-Adaptive Over-the-Air Federated Learning over Wireless Networks
J Mao, H Yang, P Qiu, J Liu, A Yener
IEEE SPAWC 2022, 2022
112022
Net-fleet: Achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data
X Zhang, M Fang, Z Liu, H Yang, J Liu, Z Zhu
Proc. ACM MobiHoc 2022, 2022
92022
Sagda: Achieving O (ϵ− 2) communication complexity in federated min-max learning
H Yang, Z Liu, X Zhang, J Liu
NeurIPS 2022, 2022
9*2022
Decentralized learning for overparameterized problems: A multi-agent kernel approximation approach
P Khanduri, H Yang, M Hong, J Liu, HT Wai, S Liu
International Conference on Learning Representations, 2021
62021
Taming Fat-Tailed ("Heavier-Tailed'' with Potentially Infinite Variance) Noise in Federated Learning
H Yang, P Qiu, J Liu
NeurIPS 2022, 2022
52022
Federated Multi-Objective Learning
H Yang, Z Liu, J Liu, C Dong, M Momma
NeurIPS 2023, 2023
22023
SAGDA: achieving O(ε-2) communication complexity in federated min-max learning
H Yang, X Zhang, Z Liu, J Liu
Proceedings of the 36th International Conference on Neural Information …, 2022
22022
On the Efficacy of Server-Aided Federated Learning against Partial Client Participation
H Yang, P Qiu, P Khanduri, J Liu
22022
Adaptive multi-hierarchical signSGD for communication-efficient distributed optimization
H Yang, X Zhang, M Fang, J Liu
2020 IEEE 21st International Workshop on Signal Processing Advances in …, 2020
12020
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
Z Li, B Ying, Z Liu, H Yang
arXiv preprint arXiv:2405.15861, 2024
2024
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation
H Yang, P Qiu, P Khanduri, M Fang, J Liu
ICML 2024, 2024
2024
Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning
T Zhou, FNU Hairi, H Yang, J Liu, T Tong, F Yang, M Momma, Y Gao
ICML 2024, 2024
2024
STIMULUS: Achieving Fast Convergence and Low Sample Complexity in Stochastic Multi-Objective Learning
Z Liu, C Dong, M Momma, S Shao, S Xu, H Yang, J Liu
2023
Understanding of Server-Assisted Federated Learning with Incomplete Client Participation
H Yang, P Qiu, P Khanduri, M Fang, J Liu
2023
The system can't perform the operation now. Try again later.
Articles 1–20