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ORCIDPeng Zheng 0002
Person information
- affiliation (PhD 2019): University of Washington, Department of Applied Mathematics, Seattle, WA, USA
Other persons with the same name
- Peng Zheng — disambiguation page
- Peng Zheng 0001 — University of California Irvine, Department of Electrical and Computer Engineering, CA, USA
- Peng Zheng 0003
![[0000-0003-2270-3439]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0003-2270-3439")
— Central South University, School of Computer Science and Engineering, Changsha, China (and 1 more) - Peng Zheng 0004 — Shanghai AI Lab, China (and 4 more)
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Journal Articles
- 2024
[j10]Aleksei Sholokhov, James V. Burke, Damian F. Santomauro, Peng Zheng, Aleksandr Y. Aravkin:
A Relaxation Approach to Feature Selection for Linear Mixed Effects Models. J. Comput. Graph. Stat. 33(1): 261-275 (2024)- 2023
- [j9]Aleksei Sholokhov, Peng Zheng, Aleksandr Y. Aravkin:
pysr3: A Python Package for Sparse Relaxed Regularized Regression. J. Open Source Softw. 8(86): 5155 (2023) - 2022
- [j8]Travis Askham, Peng Zheng, Aleksandr Y. Aravkin, J. Nathan Kutz:
Robust and Scalable Methods for the Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. 21(1): 60-79 (2022) - 2021
- [j7]Peng Zheng, Ryan Barber, Reed J. D. Sorensen, Christopher J. L. Murray, Aleksandr Y. Aravkin:
Trimmed Constrained Mixed Effects Models: Formulations and Algorithms. J. Comput. Graph. Stat. 30(3): 544-556 (2021) - [j6]Germán Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James R. Kozloski, Pablo Polosecki, Guillaume Lajoie, David D. Cox, Silvina Ponce Dawson, Guillermo A. Cecchi, Irina Rish:
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. 33(8): 2087-2127 (2021) - [j5]Peng Zheng, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin:
Estimating Shape Parameters of Piecewise Linear-Quadratic Problems. Open J. Math. Optim. 2: 1-18 (2021) - [j4]Jonathan Jonker, Peng Zheng, Aleksandr Y. Aravkin:
Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models. IEEE Trans. Autom. Control. 66(10): 4852-4857 (2021) - 2020
- [j3]Kathleen P. Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz:
A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data. IEEE Access 8: 169259-169271 (2020) - [j2]N. Benjamin Erichson, Peng Zheng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin:
Sparse Principal Component Analysis via Variable Projection. SIAM J. Appl. Math. 80(2): 977-1002 (2020) - 2019
- [j1]Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin:
A Unified Framework for Sparse Relaxed Regularized Regression: SR3. IEEE Access 7: 1404-1423 (2019)
Conference and Workshop Papers
- 2019
- [c2]Jihun Yun, Peng Zheng, Eunho Yang, Aurélie C. Lozano, Aleksandr Y. Aravkin:
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. ICML 2019: 7242-7251 - 2017
- [c1]Peng Zheng, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy:
Learning Robust Representations for Computer Vision. ICCV Workshops 2017: 1784-1791
Informal and Other Publications
- 2024
- [i5]Ariane Ducellier, Alexander Hsu, Parkes Kendrick, Bill Gustafson, Laura Dwyer-Lindgren, Christopher Murray, Peng Zheng, Aleksandr Y. Aravkin:
Uncertainty Quantification under Noisy Constraints, with Applications to Raking. CoRR abs/2407.20520 (2024) - 2019
- [i4]Kathleen P. Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz:
A unified sparse optimization framework to learn parsimonious physics-informed models from data. CoRR abs/1906.10612 (2019) - 2018
- [i3]Germán Abrevaya, Aleksandr Y. Aravkin, Guillermo A. Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Ponce Dawson:
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. CoRR abs/1805.09874 (2018) - [i2]Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin:
Sparse Relaxed Regularized Regression: SR3. CoRR abs/1807.05411 (2018) - 2017
- [i1]Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan:
Learning Robust Representations for Computer Vision. CoRR abs/1708.00069 (2017)
Coauthor Index
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