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Xinwei Zhang
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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
2262021
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
200*2022
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
832020
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
822019
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
602022
Hybrid federated learning: Algorithms and implementation
X Zhang, W Yin, M Hong, T Chen
arXiv preprint arXiv:2012.12420, 2020
162020
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
On the Connection Between Fed-Dyn and FedPD
X Zhang, M Hong
FedDyn FedPD. pdf, 2021
42021
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
3*2023
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
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
22023
Dimplementing 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
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
22018
Differentially private sgd without clipping bias: An error-feedback approach
X Zhang, Z Bu, ZS Wu, M Hong
arXiv preprint arXiv:2311.14632, 2023
12023
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
12023
Building large machine learning models from small distributed models: A layer matching approach
X Zhang, B Song, M Honarkhah, J Ding, M Hong
Workshop on Federated Learning: Recent Advances and New Challenges (in …, 2022
12022
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
12022
Pre-training Differentially Private Models with Limited Public Data
Z Bu, X Zhang, M Hong, S Zha, G Karypis
arXiv preprint arXiv:2402.18752, 2024
2024
Privacy-preserving federated learning: algorithms and guarantees
X Zhang, X Chen, B Song, P Khanduri, M Hong
Federated Learning, 57-74, 2024
2024
A Unified Framework for Understanding Distributed Optimization Algorithms: System Design and its Applications
X Zhang
University of Minnesota, 2023
2023
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