33 citations · 50 across the 13 of their papers we have counts for
13 papers
Learning Curves and Benign Overfitting of Spectral Algorithms in Large Dimensions
Weihao Lu, Qian Lin, Yingcun Xia +1
Existing large-dimensional theory for spectral algorithms resolves either the optimally tuned point or the interpolation limit, but leaves the under-regularized regime unexplored.…
Covariance Function Estimation for High-Dimensional Functional Time Series with Dual Factor Structures
Chenlei Leng, Degui Li, Hanlin Shang +1
We propose a flexible dual functional factor model for modelling high-dimensional functional time series. In this model, a high-dimensional fully functional factor parametrisation…
Dimension Reduction and MARS
Yu Liu, Degui Li, Yingcun Xia
The multivariate adaptive regression spline (MARS) is one of the popular estimation methods for nonparametric multivariate regressions. However, as MARS is based on marginal spline…
Consistency of Oblique Decision Tree and its Boosting and Random Forest
Haoran Zhan, Yu Liu, Yingcun Xia
Classification and Regression Tree (CART), Random Forest (RF) and Gradient Boosting Tree (GBT) are probably the most popular set of statistical learning methods. However, their sta…
Ensemble Projection Pursuit for General Nonparametric Regression
Haoran Zhan, Mingke Zhang, Yingcun Xia
The projection pursuit regression (PPR) has played an important role in the development of statistics and machine learning. However, when compared to other established methods like…
Accounting for correlated horizontal pleiotropy in two-sample Mendelian randomization using correlated instrumental variants
Qing Cheng, Baoluo Sun, Yingcun Xia +1
Mendelian randomization (MR) is a powerful approach to examine the causal relationships between health risk factors and outcomes from observational studies. Due to the proliferatio…