| How can machine learning aid behavioral marketing research? L Hagen, K Uetake, N Yang, B Bollinger, AJB Chaney, D Dzyabura, ... Marketing Letters 31, 361-370, 2020 | 51 | 2020 |
| Omitted variable bias of Lasso-based inference methods: A finite sample analysis K Wüthrich, Y Zhu Review of Economics and Statistics 105 (4), 982-997, 2023 | 26 | 2023 |
| Sparse linear models and l1-regularized 2SLS with high-dimensional endogenous regressors and instruments Y Zhu Journal of Econometrics 202 (2), 196-213, 2018 | 21 | 2018 |
| Inference in approximately sparse correlated random effects probit models with panel data JM Wooldridge, Y Zhu Journal of Business & Economic Statistics 38 (1), 1-18, 2020 | 20 | 2020 |
| Evaluating airline delays: the role of airline networks, schedules, and passenger demands Y Zhu Massachusetts Institute of Technology, 2008 | 20 | 2008 |
| Nonasymptotic analysis of semiparametric regression models with high-dimensional parametric coefficients Y Zhu | 16 | 2017 |
| High dimensional inference in partially linear models Y Zhu, Z Yu, G Cheng The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 13 | 2019 |
| Sparse linear models and two-stage estimation in high-dimensional settings with possibly many endogenous regressors Y Zhu arXiv preprint arXiv:1309.4193, 2013 | 5 | 2013 |
| Classes of ODE solutions: smoothness, covering numbers, implications for noisy function fitting, and the curse of smoothness phenomenon Y Zhu, M Mirzaei arXiv preprint arXiv:2011.11371, 2020 | 2 | 2020 |
| High-dimensional semiparametric selection models: estimation theory with an application to the retail gasoline market Y Zhu arXiv preprint arXiv:1411.0800, 2014 | 2 | 2014 |
| Nonparametric density estimation based on the truncated mean Y Zhu Statistics & Probability Letters 83 (2), 445-451, 2013 | 2 | 2013 |
| Statistical inference and feasibility determination: a nonasymptotic approach Y Zhu arXiv preprint arXiv:1808.07127, 2018 | 1 | 2018 |
| Consistent variable selection of the l1-regularized 2SLS with high-dimensional endogenous regressors and instruments Y Zhu Manuscript. University of California, Berkeley.(https://sites. google. com …, 2013 | 1 | 2013 |
| Phase transitions in nonparametric regressions Y Zhu Journal of Econometrics, 105640, 2024 | | 2024 |
| Information-theoretic limitations of data-based price discrimination H Xie, Y Zhu, D Shishkin arXiv preprint arXiv:2204.12723, 2022 | | 2022 |
| Data-based price discrimination: information theoretic limitations and a minimax optimal strategy. H Xie, Y Zhu CoRR, 2022 | | 2022 |
| Optimal degree of smoothness to exploit in nonparametric regressions Y Zhu arXiv preprint arXiv:2112.03626, 2021 | | 2021 |
| Bless and curse of smoothness and phase transitions in nonparametric regressions: a nonasymptotic perspective. Y Zhu CoRR, 2021 | | 2021 |
| Ordinary differential equations (ODE): metric entropy and nonasymptotic theory for noisy function fitting. Y Zhu, M Mirzaei CoRR, 2020 | | 2020 |
| Concentration Based Inference in High Dimensional Generalized Regression Models (I: Statistical Guarantees) Y Zhu | | 2018 |
Kaspar WüthrichUniversity of California, San DiegoBestätigte E-Mail-Adresse bei ucsd.edu
