Working Papers

Available upon request

1. Online Covariance Matrix Estimation in Stochastic Inexact Newton Methods
Wei Kuang, Sen Na, Michael W. Mahoney, Mihai Anitescu
A short note is accepted by 2023 NeurIPS Optimization for Machine Learning (OPT) workshop, 2023.
2. Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models
Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar
A short note is accepted by 2022 NeurIPS Higher-Order Optimization in Machine Learning (HOO) workshop, 2023.

Preprints

Under review

1. An Asymptotically Optimal Method for Constrained Stochastic Optimization
Sen Na, Yihang Gao, Michael K. Ng, Michael W. Mahoney
In submission to Annals of Statistics, 2024.
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2. Near-Optimal Performance of Stochastic Predictive Control
Sungho Shin, Sen Na, Mihai Anitescu
arXiv preprint arXiv:2210.08599, 2022.
Cite arXiv
3. Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
Sen Na, Michael W. Mahoney
arXiv preprint arXiv:2205.13687, 2022.
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Selected Recent Publications

All publications in
chronological order »

1. Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems
Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar
To appear in SIAM Journal on Optimization, 2024.
Cite arXiv
2. Convergence Analysis of Accelerated Stochastic Gradient Descent under the Growth Condition
You-Lin Chen, Sen Na, Mladen Kolar
To appear in Mathematics of Operations Research, 2023.
Cite arXiv
3. A Fast Temporal Decomposition Procedure for Long-horizon Nonlinear Dynamic Programming
Sen Na, Mihai Anitescu, Mladen Kolar
Mathematics of Operations Research, 2023.
Cite DOI arXiv
4. Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming
Sen Na, Mihai Anitescu, Mladen Kolar
Mathematical Programming, 2023.
Cite DOI arXiv
5. Superconvergence of Online Optimization for Model Predictive Control
Sen Na, Mihai Anitescu
IEEE Transactions on Automatic Control, 2023.
Cite DOI arXiv
6. Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence
Sen Na, Michał Dereziński, Michael W. Mahoney
Mathematical Programming, 2022.
Cite DOI arXiv
7. 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.
Cite DOI arXiv
8. An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
Sen Na, Mihai Anitescu, Mladen Kolar
Mathematical Programming, 2022.
Cite DOI arXiv
9. Global Convergence of Online Optimization for Nonlinear Model Predictive Control
Sen Na
Advances in Neural Information Processing Systems, 2021.
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10. High-dimensional Index Volatility Models via Stein's Identity
Sen Na, Mladen Kolar
Bernoulli, 2021.
Cite DOI arXiv
11. Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity
Sen Na, Mladen Kolar, Oluwasanmi Koyejo
Biometrika, 2020.
Cite DOI arXiv
12. Exponential Decay in the Sensitivity Analysis of Nonlinear Dynamic Programming
Sen Na, Mihai Anitescu
SIAM Journal on Optimization, 2020.
Cite DOI arXiv
13. High-dimensional Varying Index Coefficient Models via Stein's Identity
Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
Journal of Machine Learning Research, 2019.
Cite URL arXiv
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