Peng Zheng - RankMe

17 papers A* 1Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A Relaxation Approach to Feature Selection for Linear Mixed Effects Models. J. Comput. Graph. Stat. Aleksei Sholokhov, James V. Burke, Damian F. Santomauro, Peng Zheng, Aleksandr Y. Aravkin
2024	J	`jnl`	Uncertainty Quantification under Noisy Constraints, with Applications to Raking. CoRR Ariane Ducellier, Alexander W. Hsu, Parkes Kendrick, Bill Gustafson, Laura Dwyer-Lindgren, Christopher Murray, Peng Zheng, Aleksandr Y. Aravkin
2023	J	`jnl`	pysr3: A Python Package for Sparse Relaxed Regularized Regression. J. Open Source Softw. Aleksei Sholokhov, Peng Zheng, Aleksandr Y. Aravkin
2022	J	`jnl`	Robust and Scalable Methods for the Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. Travis Askham, Peng Zheng, Aleksandr Y. Aravkin, J. Nathan Kutz
2021	J	`jnl`	Efficient Robust Parameter Identification in Generalized Kalman Smoothing Models. IEEE Trans. Autom. Control. Jonathan Jonker, Peng Zheng, Aleksandr Y. Aravkin
2021	J	`jnl`	Estimating Shape Parameters of Piecewise Linear-Quadratic Problems. Open J. Math. Optim. Peng Zheng, Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin
2021	J	`jnl`	Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. 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
2021	J	`jnl`	Trimmed Constrained Mixed Effects Models: Formulations and Algorithms. J. Comput. Graph. Stat. Peng Zheng, Ryan Barber, Reed J. D. Sorensen, Christopher J. L. Murray, Aleksandr Y. Aravkin
2020	J	`jnl`	A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data. IEEE Access Kathleen P. Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz
2020	J	`jnl`	Sparse Principal Component Analysis via Variable Projection. SIAM J. Appl. Math. N. Benjamin Erichson, Peng Zheng, Krithika Manohar, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
2019	J	`jnl`	A Unified Framework for Sparse Relaxed Regularized Regression: SR3. IEEE Access Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
2019	J	`jnl`	A unified sparse optimization framework to learn parsimonious physics-informed models from data. CoRR Kathleen P. Champion, Peng Zheng, Aleksandr Y. Aravkin, Steven L. Brunton, J. Nathan Kutz
2019	A*	`conf`	Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. ICML Jihun Yun, Peng Zheng, Eunho Yang, Aurélie C. Lozano, Aleksandr Y. Aravkin
2018	J	`jnl`	Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. CoRR Germán Abrevaya, Aleksandr Y. Aravkin, Guillermo A. Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Ponce Dawson
2018	J	`jnl`	Sparse Relaxed Regularized Regression: SR3. CoRR Peng Zheng, Travis Askham, Steven L. Brunton, J. Nathan Kutz, Aleksandr Y. Aravkin
2017	—	`conf`	Learning Robust Representations for Computer Vision. ICCV Workshops Peng Zheng, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy
2017	J	`jnl`	Learning Robust Representations for Computer Vision. CoRR Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan