Publications | Xuyang Wu

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2026 4

Anderson Accelerated Asynchronous Method for Distributed Optimization TMLR
C. Li and X. Wu. Transactions on Machine Learning Research, 2026. [paper]
Anderson Acceleration for Distributed Constrained Optimization over Time-varying Networks Preprint
H. Liu and X. Wu, 2026. [paper]
An Accelerated Proximal Bundle Method with Momentum CDC
Z. Zheng, J. Yin, S. Yang, and X. Wu. IEEE Conference on Decision and Control, 2026. [paper]
Bundle EXTRA for Decentralized Optimization CDC
H. Liu, Z. Zheng, C. Li, W. Xu, and X. Wu. IEEE Conference on Decision and Control, 2026. [paper]

2025 10

From Promise to Practice: Realizing High-performance Decentralized Training ICLR
Z. Wang, J. Zhang, X. Wu, and M. Johansson. International Conference on Learning Representations, 2025. [paper]
An Asynchronous Bundle Method for Distributed Learning Problems ICLR
D. Cederberg, X. Wu, S. P. Boyd, and M. Johansson. International Conference on Learning Representations, 2025. [paper]
Historical Information Accelerates Decentralized Optimization: A Proximal Bundle Method Preprint
Z. Zhu, Y.-P. Tian, and X. Wu, 2025. [paper]
Primal-Dual Bundle Methods for Linear Equality-Constrained Problems Preprint
Z. Zheng, T. Liu, and X. Wu, 2025. [paper]
A Delay-free Adaptive Stepsize for the Incremental Aggregated Gradient Methoda> L-CSS
Z. Deng, X. Wu, and J. Lu. IEEE Control Systems Letters, 2025. [paper]
A Unified Dual Consensus Approach to Distributed Optimization with Globally-Coupled Constraints TCNS
Z. Liu, X. Wu, D. Wang, and J. Lu. IEEE Transactions on Control of Networked Systems, 2025. [paper]
Linear Output Regulation with Cooperative Parallel Operation of Multiple Actuators over Jointly Connected Switching Networks Automatica
Y. Chen, X. Wu, and T. Liu. Automatica, 2025. [paper]
Globally-Constrained Decentralized Optimization with Variable Coupling TAC
D. Wang, X. Wu, Z. Ou, and J. Lu. IEEE Transactions on Automatic Control, 2025. [paper]
Achieving Violation-free Distributed Optimization under Coupling Constraints Automatica
C. Liu, X. Tan, X. Wu, D. V. Dimarogonas, and K. H. Johansson. Automatica, 2025. [paper]
Asynchronous Distributed Optimization with Delay-free Parameters TAC
X. Wu, C. Liu, S. Magnusson, and M. Johansson. IEEE Transactions on Automatic Control, 2025. [paper]

2023 9

Delay-agnostic Asynchronous Coordinate Update Algorithm ICML
X. Wu, C. Liu, S. Magnusson, and M. Johansson. International Conference on Machine Learning, 2023. [paper]
A Regularized Fenchel Dual Gradient Method for Nonsmooth Optimization over Time-varying Networks OMS
X. Wu, K. Sou, and J. Lu. Optimization Methods and Software, 2023. [paper]
Distributed Safe Resource Allocation using Barrier Functions Automatica
X. Wu, S. Magnusson, and M. Johansson. Automatica, 2023. [paper]
Distributed Optimization with Coupling Constraints TAC
X. Wu, H. Wang, and J. Lu. IEEE Transactions on Automatic Control, 2023. [paper]
A Unifying Approximate Method of Multipliers for Distributed Composite Optimization TAC
X. Wu and J. Lu. IEEE Transactions on Automatic Control, 2023. [paper]
Delay-agnostic Asynchronous Distributed Optimization CDC
X. Wu, C. Liu, S. Magnusson, and M. Johansson. IEEE Conference on Decision and Control (invited), 2023. [paper]
Revisiting the Curvature-aided IAG: Improved Theory and Reduced Complexity IFAC
E. Berglund, S. Khirirat, X. Wu, S. Magnusson, and M. Johansson. IFAC World Congress, 2023.
Rate Analysis of Dual Averaging for Nonconvex Distributed Optimization IFAC
C. Liu, X. Wu, X. Yi, Y. Shi, and K. H. Johansson. IFAC World Congress, 2023. [paper]

2022 2

Delay-adaptive Step-sizes for Asynchronous Learning ICML
X. Wu, H. R. Feyzmahdavian, S. Magnusson, and M. Johansson. International Conference on Machine Learning, 2022. [paper]
Optimal Convergence Rates of Totally Asynchronous Optimization CDC
X. Wu, H. R. Feyzmahdavian, S. Magnusson, and M. Johansson. IEEE Conference on Decision and Control, 2022. [paper]

2021 and earlier 11

Decentralized Approximate Newton Methods for Convex Optimization on Networked Systems TCNS
H. Wei, Z. Qu, X. Wu, H. Wang, and J. Lu. IEEE Transactions on Control of Network Systems, 2021. [paper]
A Second-Order Proximal Algorithm for Consensus Optimization TAC
X. Wu, Z. Qu, and J. Lu. IEEE Transactions on Automatic Control, 2021. [paper]
A New Family of Feasible Methods for Distributed Resource Allocation CDC
X. Wu, S. Magnusson, and M. Johansson. IEEE Conference on Decision and Control (invited), 2021. [paper]
Distributed Optimization over Time-varying Networks with Minimal Connectivity L-CSS
X. Wu and J. Lu. IEEE Control Systems Letters, 2020. [paper]
A Distributed Proximal Primal-Dual Algorithm for Nonsmooth Optimization with Coupling Constraints CDC
X. Wu, H. Wang, and J. Lu. IEEE Conference on Decision and Control (invited), 2020. [paper]
Fenchel Dual Gradient Methods for Distributed Convex Optimization over Time-varying Networks TAC
X. Wu and J. Lu. IEEE Transactions on Automatic Control, 2019. [paper]
Improved Convergence Rates of P-EXTRA for Non-smooth Distributed Optimization ICCA
X. Wu and J. Lu. IEEE International Conference on Control & Automation (invited), 2019. Best Student Paper Finalist. [paper]
Finite-Time-Consensus-Based Methods for Distributed Optimization CCC
Z. Qu, X. Wu, and J. Lu. Chinese Control Conference (invited), 2019. [paper]
Fenchel Dual Gradient Methods Enabling a Smoothing Technique for Nonsmooth Distributed Convex Optimization CDC
X. Wu, K. C. Sou, and J. Lu. IEEE Conference on Decision and Control (invited), 2018. [paper]
An Approximately-Zero-Gradient-Sum Algorithm for Consensus Optimization ICARCV
H. Wei, Z. Qu, X. Wu, H. Wang, and J. Lu. International Conference on Control, Automation, Robotics and Vision (invited), 2018. [paper]
Deterministic Coordinate Descent Algorithms for Smooth Convex Optimization CDC
X. Wu and J. Lu. IEEE Conference on Decision and Control, 2017. [paper]
Fenchel Dual Gradient Methods for Distributed Convex Optimization over Time-varying Networks CDC
X. Wu and J. Lu. IEEE Conference on Decision and Control, 2017. [paper]