| Stochastic gradient descent in correlated settings: A study on gaussian processes H Chen, L Zheng, R Al Kontar, G Raskutti Advances in neural information processing systems 33, 2722-2733, 2020 | 40 | 2020 |
| Testing for high-dimensional network parameters in auto-regressive models L Zheng, G Raskutti | 22 | 2019 |
| Optimal high-order tensor svd via tensor-train orthogonal iteration Y Zhou, AR Zhang, L Zheng, Y Wang IEEE transactions on information theory 68 (6), 3991-4019, 2022 | 21 | 2022 |
| Interpretable machine learning for discovery: Statistical challenges and opportunities GI Allen, L Gan, L Zheng Annual Review of Statistics and Its Application 11, 2023 | 15 | 2023 |
| Inference for interpretable machine learning: fast, model-agnostic confidence intervals for feature importance L Gan, L Zheng, GI Allen arXiv preprint arXiv:2206.02088, 2022 | 5 | 2022 |
| Low-rank covariance completion for graph quilting with applications to functional connectivity A Chang, L Zheng, GI Allen arXiv preprint arXiv:2209.08273, 2022 | 4 | 2022 |
| Gaussian process parameter estimation using mini-batch stochastic gradient descent: convergence guarantees and empirical benefits H Chen, L Zheng, R Al Kontar, G Raskutti Journal of Machine Learning Research 23 (227), 1-59, 2022 | 3 | 2022 |
| Graphical Model Inference with Erosely Measured Data L Zheng, GI Allen Journal of the American Statistical Association, 1-12, 2023 | 2 | 2023 |
| Model-agnostic confidence intervals for feature importance: A fast and powerful approach using minipatch ensembles L Gan, L Zheng, GI Allen arXiv preprint arXiv:2206.02088, 2022 | 2 | 2022 |
| Gaussian process inference using mini-batch stochastic gradient descent: Convergence guarantees and empirical benefits H Chen, L Zheng, RA Kontar, G Raskutti arXiv preprint arXiv:2111.10461, 2021 | 2 | 2021 |
| Context-dependent self-exciting point processes: models, methods, and risk bounds in high dimensions L Zheng, G Raskutti, R Willett, B Mark arXiv preprint arXiv:2003.07429, 2020 | 2 | 2020 |
| High-dimensional multi-class classification with presence-only data L Zheng, G Raskutti arXiv preprint arXiv:2304.09305, 2023 | 1 | 2023 |
| Learning Gaussian Graphical Models with Differing Pairwise Sample Sizes L Zheng, GI Allen ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 1 | 2022 |
| A Low-Rank Tensor Completion Approach for Imputing Functional Neuronal Data from Multiple Recordings L Zheng, ZT Rewolinski, GI Allen 2022 IEEE Data Science and Learning Workshop (DSLW), 1-6, 2022 | 1 | 2022 |
| Joint Semi-Symmetric Tensor PCA for Integrating Multi-modal Populations of Networks J Liu, L Zheng, Z Zhang, GI Allen arXiv preprint arXiv:2312.14416, 2023 | | 2023 |
| Nonparanormal graph quilting with applications to calcium imaging A Chang, L Zheng, G Dasarathy, GI Allen Stat 12 (1), e623, 2023 | | 2023 |
| Learning Dependence from Large-scale Data: Addressing Statistical and Optimization Challenges L Zheng The University of Wisconsin-Madison, 2021 | | 2021 |
| Context-dependent networks in multivariate time series: models, methods, and risk bounds in high dimensions L Zheng, G Raskutti, R Willett, B Mark Journal of Machine Learning Research 22 (216), 1-88, 2021 | | 2021 |
Genevera I. AllenAssociate Professor, Electrical and Computer Engineering, Statistics, and Computer Science, RiceVerified email at rice.edu
