Publications

1. Online Inference of Constrained Optimization: Primal-Dual Optimality and Sequential Quadratic Programming
Yihang Gao, Michael K. Ng, Michael W. Mahoney, Sen Na
arXiv preprint arXiv:2512.08948, 2025.
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2. Derivative-Free Sequential Quadratic Programming for Equality-Constrained Stochastic Optimization
Sen Na
arXiv preprint arXiv:2510.22458, 2025.
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3. Overlapping Schwarz Scheme for Linear-Quadratic Programs in Continuous Time
Hongli Zhao, Mihai Anitescu, Sen Na
arXiv preprint arXiv:2510.04478, 2025.
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4. Online Statistical Inference for Proximal Stochastic Gradient Descent under Markovian Sampling
Xinchen Du, Sen Na
A short version has been accepted in NeurIPS 2025 COML Workshop, 2025.
5. Statistical Inference of Constrained Model Estimation via Derivative-Free Stochastic Sequential Quadratic Programming
Jianliang Ye, Sen Na
A short version has been accepted in NeurIPS 2025 COML Workshop, 2025.
6. Near-Optimal Performance of Stochastic Model Predictive Control
Sungho Shin, Sen Na, Mihai Anitescu
To appear in Mathematics of Operations Research, 2025.
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7. Online Statistical Inference of Constrained Stochastic Optimization via Random Scaling
Xinchen Du, Wanrong Zhu, Wei Biao Wu, Sen Na
arXiv preprint arXiv:2505.18327, 2025.
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8. Online Covariance Estimation in Nonsmooth Stochastic Approximation
Liwei Jiang, Abhishek Roy, Krishna Balasubramanian, Damek Davis, Dmitriy Drusvyatskiy, Sen Na
Conference on Learning Theory, 2025.
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9. High Probability Complexity Bounds of Trust-Region Stochastic Sequential Quadratic Programming with Heavy-Tailed Noise
Yuchen Fang, Javad Lavaei, Sen Na
arXiv preprint arXiv:2503.19091, 2025.
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10. Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
Sen Na, Michael W. Mahoney
Journal of Machine Learning Research, 2025.
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11. Online Covariance Matrix Estimation in Sketched Newton Methods
Wei Kuang, Mihai Anitescu, Sen Na
arXiv preprint arXiv:2502.07114, 2025.
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12. Panda: partially approximate newton methods for distributed minimax optimization with unbalanced dimensions
Minheng Xiao, Chengchang Liu, Cheng Chen, John C.S. Lui, Sen Na
Machine Learning, 2025.
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13. Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models
Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar
arXiv preprint arXiv:2409.15734, 2024.
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14. Physics-Informed Neural Networks with Trust-Region Sequential Quadratic Programming
Xiaoran Cheng, Sen Na
arXiv preprint arXiv:2409.10777, 2024.
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15. Distributed Sequential Quadratic Programming with Overlapping Graph Decomposition and Exact Augmented Lagrangian
Runxin Ni, Sen Na, Sungho Shin, Mihai Anitescu
arXiv preprint arXiv:2402.17170, 2024.
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16. Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems
Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar
SIAM Journal on Optimization, 2024.
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17. Convergence Analysis of Accelerated Stochastic Gradient Descent under the Growth Condition
You-Lin Chen, Sen Na, Mladen Kolar
Mathematics of Operations Research, 2023.
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18. Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching
Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar
International Conference on Machine Learning, 2023.
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19. A Fast Temporal Decomposition Procedure for Long-horizon Nonlinear Dynamic Programming
Sen Na, Mihai Anitescu, Mladen Kolar
Mathematics of Operations Research, 2023.
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20. Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming
Sen Na, Mihai Anitescu, Mladen Kolar
Mathematical Programming, 2023.
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21. Superconvergence of Online Optimization for Model Predictive Control
Sen Na, Mihai Anitescu
IEEE Transactions on Automatic Control, 2023.
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22. Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence
Sen Na, Michał Dereziński, Michael W. Mahoney
Mathematical Programming, 2022.
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23. On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control
Sen Na, Sungho Shin, Mihai Anitescu, Victor M. Zavala
IEEE Transactions on Automatic Control, 2022.
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24. SFGAE: a Self-feature-based Graph Autoencoder Model for miRNA--disease Associations Prediction
Mingyuan Ma, Sen Na, Xiaolu Zhang, Congzhou Chen, Jin Xu
Briefings in Bioinformatics, 2022.
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25. An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
Sen Na, Mihai Anitescu, Mladen Kolar
Mathematical Programming, 2022.
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26. Global Convergence of Online Optimization for Nonlinear Model Predictive Control
Sen Na
Advances in Neural Information Processing Systems, 2021.
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27. The Graph-Based Behavior-Aware Recommendation for Interactive News
Mingyuan Ma, Sen Na, Hongyu Wang, Congzhou Chen, Jin Xu
Applied Intelligence, 2021.
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28. High-dimensional Index Volatility Models via Stein's Identity
Sen Na, Mladen Kolar
Bernoulli, 2021.
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29. AEGCN: An Autoencoder-Constrained Graph Convolutional Network
Mingyuan Ma, Sen Na, Hongyu Wang
Neurocomputing, 2021.
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30. Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity
Sen Na, Mladen Kolar, Oluwasanmi Koyejo
Biometrika, 2020.
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31. Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
International Conference on Machine Learning, 2020.
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32. Exponential Decay in the Sensitivity Analysis of Nonlinear Dynamic Programming
Sen Na, Mihai Anitescu
SIAM Journal on Optimization, 2020.
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33. High-dimensional Varying Index Coefficient Models via Stein's Identity
Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
Journal of Machine Learning Research, 2019.
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