Interface of PDEs and Machine Learning
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Defending Against Diverse Attacks in Federated Learning Through Consensus-Based Bi-Level Optimization [pdf]
Nicolás García Trillos, Aditya Kumar Akash, Sixu Li, Konstantin Riedl, Yuhua Zhu*.
Philosophical Transactions A, to appear, 2025.
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CB2O: Consensus-Based Bi-Level Optimization [pdf]
Nicolás García Trillos, Sixu Li, Konstantin Riedl, Yuhua Zhu*.
Preprint, 2025.
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An Interacting Particle Consensus Method for Constrained Global Optimization [pdf]
Jose Carrillo, Shi Jin, Haoyu Zhang, Yuhua Zhu*.
Preprint, 2024.
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FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization. [pdf]
Jose A. Carrillo, Nicolas Garcia Trillos, Sixu Li, Yuhua Zhu*.
Journal of Machine Learning Research (JMLR), 2024.
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Why Resampling Outperforms Reweighting for Correcting Sampling Bias with Stochastic Gradients. [pdf]
Jing An, Lexing Ying, Yuhua Zhu*.
International Conference on Learning Representations (ICLR), 2021.
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A Sharp Convergence Rate for a Model Equation of the Asynchronous Stochastic Gradient Descent. [pdf]
Yuhua Zhu, Lexing Ying.
Communications in Mathematical Sciences, 19(3), 851-863, 2020.
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On Large Batch Training and Sharp Minima: A Fokker-Planck perspective. [pdf]
Xiaowu Dai and Yuhua Zhu*.
Journal of Statistical Theory and Practice (JSTP), special issue on "Advances in Deep Learning", 2020.
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A Consensus-Based Global Optimization Method for High Dimensional Machine Learning Problems. [pdf]
Jose Carrillo, Shi Jin, Lei Li and Yuhua Zhu*
ESAIM: Control, Optimisation and Calculus of Variations 27, S5, 2020.
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Borrowing From the Future: An Attempt to Address Double Sampling. [pdf]
Yuhua Zhu and Lexing Ying.
Mathematical and Scientific Machine Learning, PMLR 107:246-268, 2020.
*: Alphabetical authorship.