18 citations · 52 across the 12 of their papers we have counts for
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stat.ML2019
Low Rank Approximation for Smoothing Spline via Eigensystem Truncation
Danqing Xu, Yuedong Wang
Smoothing splines provide a powerful and flexible means for nonparametric estimation and inference. With a cubic time complexity, fitting smoothing spline models to large data is c…
stat.ME2019
Combining Smoothing Spline with Conditional Gaussian Graphical Model for Density and Graph Estimation
Runfei Luo, Anna Liu, Yuedong Wang
Multivariate density estimation and graphical models play important roles in statistical learning. The estimated density can be used to construct a graphical model that reveals con…
math.ST2019
Smoothing Spline Semiparametric Density Models
Jian Shi, Jiahui Yu, Anna Liu +1
Density estimation plays a fundamental role in many areas of statistics and machine learning. Parametric, nonparametric and semiparametric density estimation methods have been prop…