9 citations · 16 across the 7 of their papers we have counts for
8 papers
On the limitations of data-based price discrimination
Haitian Xie, Ying Zhu, Denis Shishkin
The classic third degree price discrimination (3PD) model requires the knowledge of the distribution of buyer valuations and the covariate to set the price conditioned on the covar…
Phase transitions in nonparametric regressions
Ying Zhu
When the unknown regression function of a single variable is known to have derivatives up to the th order bounded in absolute values by a common constant everywhere or a.e.…
Classes of ODE solutions: smoothness, covering numbers, implications for noisy function fitting, and the curse of smoothness phenomenon
Ying Zhu, Mozhgan Mirzaei
Many numerical methods for recovering ODE solutions from data rely on approximating the solutions using basis functions or kernel functions under a least square criterion. The accu…
Omitted variable bias of Lasso-based inference methods: A finite sample analysis
Kaspar Wuthrich, Ying Zhu
We study the finite sample behavior of Lasso-based inference methods such as post double Lasso and debiased Lasso. We show that these methods can exhibit substantial omitted variab…
Variation entropy: a continuous local generalization of the TVD property using entropy principles
M. ten Eikelder, I. Akkerman
This paper presents the notion of a variation entropy. This concept is an entropy framework for the gradient of the solution of a conservation law instead of on the solution itself…
High Dimensional Inference in Partially Linear Models
Ying Zhu, Zhuqing Yu, Guang Cheng
We propose two semiparametric versions of the debiased Lasso procedure for the model , where is high dimensional but sparse (exactly or approxi…
High-Dimensional Semiparametric Selection Models: Estimation Theory with an Application to the Retail Gasoline Market
Ying Zhu
This paper proposes a multi-stage projection-based Lasso procedure for the semiparametric sample selection model in high-dimensional settings under a weak nonparametric restriction…
Sparse Linear Models and Two-Stage Estimation in High-Dimensional Settings with Possibly Many Endogenous Regressors
Ying Zhu
This paper explores the validity of the two-stage estimation procedure for sparse linear models in high-dimensional settings with possibly many endogenous regressors. In particular…