19 citations · 20 across the 4 of their papers we have counts for
4 papers
Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data
Xi Chen, Ye Luo, Martin Spindler
In this paper we develop a data-driven smoothing technique for high-dimensional and non-linear panel data models. We allow for individual specific (non-linear) functions and estima…
Estimation and Inference of Treatment Effects with -Boosting in High-Dimensional Settings
Jannis Kueck, Ye Luo, Martin Spindler +1
Empirical researchers are increasingly faced with rich data sets containing many controls or instrumental variables, making it essential to choose an appropriate approach to variab…
Boosting for Economic Applications
Ye Luo, Martin Spindler
In the recent years more and more high-dimensional data sets, where the number of parameters is high compared to the number of observations or even larger, are available fo…
High-Dimensional Boosting: Rate of Convergence
Ye Luo, Martin Spindler, Jannis Kück
Boosting is one of the most significant developments in machine learning. This paper studies the rate of convergence of Boosting, which is tailored for regression, in a high-d…