Support vector machine (SVM) is a popular classifier known for accuracy,...
Subsampling methods aim to select a subsample as a surrogate for the obs...
Smoothing splines have been used pervasively in nonparametric regression...
With rapid advances in information technology, massive datasets are coll...
Sparse coding aims to model data vectors as sparse linear combinations o...
With the rapid development of quantum computers, quantum algorithms have...
This paper studies the estimation of large-scale optimal transport maps
...
Background: Extensive clinical evidence suggests that a preventive scree...
We consider a measurement constrained supervised learning problem, that ...
Sufficient dimension reduction is used pervasively as a supervised dimen...
Optimal transport has been one of the most exciting subjects in mathemat...
Large samples have been generated routinely from various sources. Classi...
We consider the problem of approximating smoothing spline estimators in ...
We consider the problem of comparing probability densities between two
g...
Testing the hypothesis of parallelism is a fundamental statistical probl...