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Xinwei Zhang
Xinwei Zhang
University of Southern California
Verified email at umn.edu - Homepage
Title
Cited by
Cited by
Year
Fedpd: A federated learning framework with adaptivity to non-iid data
X Zhang, M Hong, S Dhople, W Yin, Y Liu
IEEE Transactions on Signal Processing 69, 6055-6070, 2021
3252021
FedBCD: A communication-efficient collaborative learning framework for distributed features
Y Liu, X Zhang, Y Kang, L Li, T Chen, M Hong, Q Yang
IEEE Transactions on Signal Processing 70, 4277-4290, 2022
278*2022
Understanding clipping for federated learning: Convergence and client-level differential privacy
X Zhang, X Chen, M Hong, ZS Wu, J Yi
International Conference on Machine Learning, ICML 2022, 2022
1112022
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
Hybrid federated learning: Algorithms and implementation
X Zhang, W Yin, M Hong, T Chen
arXiv preprint arXiv:2012.12420, 2020
33*2020
Fedavg converges to zero training loss linearly for overparameterized multi-layer neural networks
B Song, P Khanduri, X Zhang, J Yi, M Hong
International Conference on Machine Learning, 32304-32330, 2023
10*2023
Differentially private sgd without clipping bias: An error-feedback approach
X Zhang, Z Bu, ZS Wu, M Hong
arXiv preprint arXiv:2311.14632, 2023
92023
Indoor position control of a quadrotor uav with monocular vision feedback
X Zhang, Y Du, F Chen, L Qin, Q Ling
2018 37th Chinese Control Conference (CCC), 9760-9765, 2018
92018
Glasu: A communication-efficient algorithm for federated learning with vertically distributed graph data
X Zhang, M Hong, J Chen
arXiv preprint arXiv:2303.09531, 2023
72023
On the connection between fed-dyn and fedpd
X Zhang, M Hong
FedDyn_FedPD. pdf, 2021
62021
Understanding a class of decentralized and federated optimization algorithms: A multirate feedback control perspective
X Zhang, M Hong, N Elia
SIAM Journal on Optimization 33 (2), 652-683, 2023
42023
Pre-training differentially private models with limited public data
Z Bu, X Zhang, S Zha, M Hong, G Karypis
Advances in Neural Information Processing Systems 37, 94652-94683, 2024
32024
Addax: Memory-efficient fine-tuning of language models with a combination of forward-backward and forward-only passes
Z Li, X Zhang, M Razaviyayn
5th Workshop on practical ML for limited/low resource settings, 2024
3*2024
A sum-of-squares optimization method for learning and controlling photovoltaic systems
X Zhang, V Purba, M Hong, S Dhople
2020 American Control Conference (ACC), 2376-2381, 2020
32020
State estimation of autonomous rotorcraft MAVs under indoor environments
Y Du, X Zhang, L Qin, G Wu, Q Ling
2018 Chinese Control And Decision Conference (CCDC), 4420-4424, 2018
32018
Doppler: Differentially private optimizers with low-pass filter for privacy noise reduction
X Zhang, Z Bu, M Hong, M Razaviyayn
arXiv preprint arXiv:2408.13460, 2024
22024
Building Large Models from Small Distributed Models: A Layer Matching Approach
X Zhang, B Song, M Honarkhah, J Ding, M Hong
2024 IEEE 13rd Sensor Array and Multichannel Signal Processing Workshop (SAM …, 2024
2*2024
A stochastic multi-rate control framework for modeling distributed optimization algorithms
X Zhang, M Hong, S Dhople, N Elia
International conference on machine learning, 26206-26222, 2022
22022
Implementing first-order optimization methods: Algorithmic considerations and bespoke microcontrollers
X Zhang, J Sartori, M Hong, S Dhople
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 296-300, 2019
22019
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Articles 1–20